Global Journal of Research in Engineering

Online ISSN : 2249-4596 Print ISSN : 0975-5861 DOI : 10.17406/GJRE

Smart Solar Charge Controller Application of Short-Term Load

Mitigation on Conducted Emission Performance Analysis of Enhanced

VOLUME 17 ISSUE 2 VERSION1.0

Global Journal of Researches in Engineering: F Electrical and Electronics Engineering

Global Journal of Researches in Engineering: F Electrical and Electronics Engineering Volume 17 Issue 2 (Ver. 1.0)

Open Association of Research Society

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Dr. Ren-Jye Dzeng Dr. Eric M. Lui

Professor Ph.D., Civil Engineering Structural Engineering National Chiao-Tung University Department of Civil Taiwan & Environmental Engineering Dean of General Affairs Syracuse University, USA Ph.D., Civil & Environmental Engineering University of Michigan, USA

Dr. Ephraim Suhir Dr. Zhou Yufeng

Ph.D., Dept. of Mechanics and Mathematics, Ph.D. Mechanical Engineering & Materials Science, Moscow University Duke University, US Moscow, Russia Assistant Professor College of Engineering, Bell Laboratories Nanyang Technological University, Singapore Physical Sciences and Engineering Research Division, USA

Dr. Pangil Choi Dr. Pallav Purohit

Ph.D. Ph.D. Energy Policy and Planning Department of Civil, Environmental, and Construction Indian Institute of Technology (IIT), Delhi Engineering Research Scientist, Texas Tech University, US International Institute for Applied Systems Analysis (IIASA), Austria

Dr. Iman Hajirasouliha Dr. Zi Chen

Ph.D. in Structural Engineering Ph.D. Department of Mechanical & Aerospace Associate Professor, Engineering, Department of Civil and Structural Engineering, Princeton University, US University of Sheffield, UK Assistant Professor, Thayer School of Engineering, Dartmouth College, Hanover, US

Dr. Wenfang Xie Dr. Giacomo Risitano,

Ph.D., Department of Electrical Engineering, Ph.D., Industrial Engineering at University of Perugia Hong Kong Polytechnic University, (Italy) Department of Automatic Control, "Automotive Design" at Engineering Department of Beijing University of Aeronautics and Astronautics, China Messina University (Messina) Italy. Dr. Joaquim Carneiro Dr. Maurizio Palesi

Ph.D. in Mechanical Engineering, Ph.D. in Computer Engineering, Faculty of Engineering, University of Catania University of Porto(FEUP), Faculty of Engineering and Architecture University of Minho, Italy Department of Physics, Portugal

Dr. Hai-Wen Li Dr. Cesar M. A. Vasques

Ph.D., Materials Engineering Ph.D., Mechanical Engineering Kyushu University Department of Mechanical Engineering Fukuoka School of Engineering, Polytechnic of Porto Guest Professor at Aarhus University, Japan Porto, Portugal

Dr. Wei-Hsin Chen Dr. Stefano Invernizzi

Ph.D., National Cheng Kung University Ph.D. in Structural Engineering Department of Aeronautics Technical University of Turin, and Astronautics, Taiwan Department of Structural, Geotechnical and Building Engineering, Italy

Dr. Saeed Chehreh Chelgani Dr. T.S. Jang

Ph.D. in Mineral Processing Ph.D. Naval Architecture and Ocean Engineering University of Western Ontario, Seoul National University, Korea Adjunct professor, Director, Arctic Engineering Research Center, Mining engineering and Mineral processing The Korea Ship and Offshore Research Institute, University of Michigan Pusan National University, South Korea

Belen Riveiro Dr. Jun Wang

Ph.D., Ph.D. in Architecture, University of Hong Kong, China School of Industrial Engineering Urban Studies University of Vigo, Spain City University of Hong Kong, China

Dr. Bin Chen Dr. Salvatore Brischetto

B.Sc., M.Sc., Ph.D., Xi’an Jiaotong University, China. Ph.D. in Aerospace Engineering, Polytechnic University of State Key Laboratory of Multiphase Flow in Power Turin and Engineering in Mechanics, Paris West University Nanterre La Défense Xi’an Jiaotong University, China Department of Mechanical and Aerospace Engineering, Polytechnic University of Turin, Italy

Dr. Francesco Tornabene Dr. Wesam S. Alaloul

Ph.D. in Structural Mechanics, University of Bologna B.Sc., M.Sc., Professor Department of Civil, Chemical, Environmental Ph.D. in Civil and Environmental Engineering, and Materials Engineering University Technology Petronas, Malaysia University of Bologna, Italy

Dr. Togay Ozbakkaloglu Dr. Sofoklis S. Makridis

B.Sc. in Civil Engineering B.Sc(Hons), M.Eng, Ph.D. Ph.D. in Structural Engineering, University of Ottawa, Professor Department of Mechanical Engineering Canada University of Western Macedonia, Greece Senior Lecturer University of Adelaide, Australia

Dr. Paolo Veronesi Dr. Ananda Kumar Palaniappan

Ph.D., Materials Engineering B.Sc., MBA, MED, Ph.D. in Civil and Environmental Institute of Electronics, Italy Engineering, President of the master Degree in Materials Engineering Ph.D. University of Malaya, Malaysia Dept. of Engineering, Italy University of Malaya, Malaysia

Dr. Maria Daniela Dr. Zhen Yuan

Ph.D. in Aerospace Science and Technologies B.E., Ph.D. in Mechanical Engineering Second University of Naples University of Sciences and Technology of China, China Research Fellow University of Naples “Federico II”, Italy Professor, Faculty of Health Sciences, University of Macau, China

Dr. Charles-Darwin Annan Dr. Hugo Silva

Ph.D., Associate Professor Professor Civil and Water Engineering University Laval, University of Minho Canada Department of Civil Engineering Ph.D., Civil Engineering

University of Minho, Portugal

Dr. Stefano Mariani Dr. Jui-Sheng Chou

Associate Professor Ph.D. University of Texas at Austin, U.S.A. Structural Mechanics Department of Civil and Construction Engineering Department of Civil National Taiwan University of Science and Technology and Environmental Engineering, (Taiwan Tech) Ph.D., in Structural Engineering Polytechnic University of Milan, Italy Dr. Shaoping Xiao Dr. Fausto Gallucci

BS, MS Associate Professor Ph.D. Mechanical Engineering, Northwestern University Chemical Process Intensification (SPI) The University of Iowa Faculty of Chemical Department of Mechanical and Industrial Engineering Engineering and Chemistry Center for Computer-Aided Design Assistant Editor International J. Hydrogen Energy, Netherlands

Dr. Vladimir Gurao Prof. (LU) Prof. (UoS) Dr. Miklas Scholz

Associate Professor Cand Ing, BEng (equiv), PgC, MSc, Ph.D., CWEM, CEnv, Ph.D. in Mechanical / CSci, CEng, Aerospace Engineering FHEA, FIEMA, FCIWEM, FICE, Fellow of IWA, University of Miami VINNOVA Fellow, Marie Curie Senior Fellow, Engineering Technology Chair in Civil Engineering (UoS) Wetland systems, sustainable drainage, and water quality

Dr. Adel Al Jumaily Dr. Houfa Shen

Ph.D. Electrical Engineering (AI) Ph.D. Manufacturing Engineering, Mechanical Engineering, Faculty of Engineering and IT Structural Engineering University of Technology, Sydney Department of Mechanical Engineering Tsinghua University, China

Dr. A. Stegou-Sagia Dr. Kitipong Jaojaruek

Ph.D. Mechanical Engineering, Environmental B. Eng, M. Eng Engineering School of Mechanical Engineering D. Eng (Energy Technology, Asian Institute of National Technical University of Athens Technology). Kasetsart University Kamphaeng Saen (KPS) Campus Energy Research Laboratory of Mechanical Engineering

Dr. Jalal Kafashan Dr. Haijian Shi

Mechanical Engineering Ph.D. Civil Engineering Division of Mechatronics Structural Engineering KU Leuven, BELGIUM Oakland, CA, United States

Dr. Omid Gohardani Dr. Burcin Becerik-Gerber

Ph.D. Senior Aerospace/Mechanical/ University of Southern Californi Aeronautical Engineering professional Ph.D. in Civil Engineering M.Sc. Mechanical Engineering DDes from Harvard University M.Sc. Aeronautical Engineering M.S. from University of California, Berkeley B.Sc. Vehicle Engineering M.S. from Istanbul Technical University Orange County, California, US Web: i-lab.usc.edu

Dr. Maciej Gucma Dr. Balasubramani R

Asistant Professor, Maritime Univeristy of Szczecin Ph.D., (IT) in Faculty of Engg. & Tech. Szczecin, Poland Professor & Head, Dept. of ISE at NMAM Institute of Ph.D.. Eng. Master Mariner Technology Web: www.mendeley.com/profiles/maciej-gucma/

Dr. Vivek Dubey(HON.) Dr. Minghua He Department of Civil Engineering MS (Industrial Engineering), Tsinghua University MS (Mechanical Engineering) Beijing, 100084, China University of Wisconsin FICCT Editor-in-Chief, US [email protected]

Dr. Ye Tian Dr. Diego González-Aguilera

Ph.D. Electrical Engineering Ph.D. Dep. Cartographic and Land Engineering, The Pennsylvania State University University of Salamanca, Ávila, Spain 121 Electrical Engineering East University Park, PA 16802, US

Dr. Alex W. Dawotola Dr. Fentahun Moges Kasie

Hydraulic Engineering Section, Department of mechanical & Industrial Engineering, Delft University of Technology, Institute of technology Stevinweg, Delft, Netherlands Hawassa University Hawassa, Ethiopia

Dr. M. Meguellati Dr. Ciprian LĂPUȘAN

Department of Electronics, Ph. D in Mechanical Engineering University of Batna, Batna 05000, Algeria Technical University of Cluj-Napoca Cluj-Napoca (Romania)

Dr. Zhibin Lin Dr. Chao Wang

Center for Infrastructure Engineering Studies Ph.D. in Computational Mechanics Missouri University of Science and Technology Rosharon, TX, ERL, 500 W. 16th St. Rolla, US Missouri 65409, US

Dr. Shun-Chung Lee Hiroshi Sekimoto

Department of Resources Engineering, Professor Emeritus National Cheng Kung University, Taiwan Tokyo Institute of Technology, Japan Ph.D., University of California, Berkeley

Dr. Philip T Moore Dr. Steffen Lehmann

Ph.D., Graduate Faculty of Creative and Master Supervisor Cultural Industries School of Information PhD, AA Dip Science and engineering University of Portsmouth, UK Lanzhou University, China

Dr. Gordana Colovic Dr. Yudong Zhang

B.Sc Textile Technology, M.Sc. Technical Science B.S., M.S., Ph.D. Signal and Information Processing, Ph.D. in Industrial management. Southeast University The College of Textile – Design, Technology and Professor School of Information Science and Technology at Management, Belgrade, Serbia Nanjing Normal University, China

Dr. Xianbo Zhao Dr. Philip G. Moscoso

Ph.D. Department of Building, Technology and Operations Management National University of Singapore, Singapore, IESE Business School, University of Navarra Senior Lecturer, Central Queensland University, Australia Ph.D in Industrial Engineering and Management, ETH Zurich M.Sc. in Chemical Engineering, ETH Zurich Link: Philip G. Moscoso personal webpage

Contents of the Issue

i. Copyright Notice ii. Editorial Board Members iii. Chief Author and Dean iv. Contents of the Issue

1. Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station. 1-12 2. Design and Construction of a Microcontroller based Smart Solar Charge Controller for Automatic Brightness Controlling of PV based Street Light. 13-20 3. Modelling and Simulation of Microcode based Built-In Self Test Technology for Multiported Memory. 21-26 4. Modeling and Mitigation on Conducted Emission for Switch Mode Power Supply. 27 -35 5. Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram. 37- 47 6. Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric. 49- 55

v. Fellows vi. Auxiliary Memberships vii. Process of Submission of Research Paper viii. Preferred Author Guidelines ix. Index

Global Journal of Researches in Engineering: F Electrical and Electronics Engineering Volume 17 Issue 2 Version 1.0 Year 2017 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4596 & Print ISSN: 0975-5861

Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station By Mishuk Mitra, Metali Rani Datta, Chinmoy Mallick & Atia Rahman University of Asia Pacific (UAP) Abstract- Energy is one of the important key factors to realize better socioeconomic development of a society and electrical energy is the most common form of energy for urban area both in commercials and residences. The instantaneous nature of electricity has made it different from other commodities as it has to be consumed just after the moment of generation. So, from generation parties to consumers at every stage of modern electricity grid it is every important to ensure the balance of consumption and production to achieve sustainability and reliability of the grid. Load forecasting is an important component for power system energy management system. Precise load forecasting helps the electric utility to make unit commitment decisions, reduces spinning reserve capacity and schedule device maintenance plan properly. Keywords: artificial neural network (ANN), feed-forward neural network (FNN), renewable energy source (RES), photo voltaic (PV). base transceiver station (BTS), short term load forecasting (STLF), support vector machine (SVM), expert system (ES). GJRE-F Classification: FOR Code: 090699

ApplicationofShortTermLoadForecastingforOptimizingtheStorageDevicesofaBaseStation

Strictly as per the compliance and regulations of :

© 2017. Mishuk Mitra, Metali Rani Datta, Chinmoy Mallick & Atia Rahman. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by- nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

Mishuk Mitra α, Metali Rani Datta σ, Chinmoy Mallick ρ & Atia Rahman Ѡ

Abstract- Energy is one of the important key factors to realize trend and variations in the data, use of clustering to get better socioeconomic development of a society and electrical more insight in intraday correlation [3]. energy is the most common form of energy for urban area both in commercials and residences. The instantaneous b) Forecasting of Consumption & Storage Device 201 nature of electricity has made it different from other Scheduling Year commodities as it has to be consumed just after the moment To schedule the storage devices, it is very of generation. So, from generation parties to consumers at crucial to have prior knowledge about electricity 1 every stage of modern electricity grid it is every important to consumption on day-ahead. Therefore, short-term ensure the balance of consumption and production to achieve forecasting is an important step to ensure better sustainability and reliability of the grid. Load forecasting is an scheduling of the storage devices [4]. Pre-processed important component for power system energy management system. Precise load forecasting helps the electric utility to data is used to evaluate the performance of the I ersion make unit commitment decisions, reduces spinning reserve forecasting models. Initially two forecasting models, capacity and schedule device maintenance plan properly. It ANN is chosen to forecast the consumption profile. This also reduces the generation cost and increases reliability of model is evaluated with respect to some evaluation ue II V power systems. In this work, an artificial neural network for criterion. The use of load forecasting is widely accepted short term load forecasting is demonstrated. Based on the as operational aid for the control the electric power time and similar previous day load, artificial neural network system as well as to enhance consumer participation in model is built, which are eventually used for the short-term local energy market through providing financial benefits. load forecasting. The aim of this work is to describe the The forecasted consumption profile of a base development and evaluation of a forecasting model to station will be used to achieve optimum scheduling of schedule the onsite storage devices. The evaluated model is Volume XVII Iss able to predict the day-ahead electricity demand of a storage devices [5]. The main idea is to utilize the

traditional base unit in order to schedule the storage devices. surplus of PV generated energy after mitigating self- () Keywords: artificial neural network (ANN), feed-forward consumption. If a particular consumer can have an idea neural network (FNN), renewable energy source (RES), about the level of stored energy, it is possible to utilize photo voltaic (PV). base transceiver station (BTS), short the energy in various way like, load shifting, include term load forecasting (STLF), support vector machine some flexible loads to consume the extra energy, valley (SVM), expert system (ES). filling etc. However, for this research our target is to feed the extra stored energy in local market, so that the I. Introduction consumer can have some financial benefits from the he process of achieving this research is mainly trading.

divided into two main parts: assessing the Researches in Engineering II. Methodology T forecasting model and scheduling of storage device [1]. The modelling and simulation is performed in The research approaches are selection and MATLAB. description of the electricity consumption data and the of nal different variables, processing and detection of missing our a) Data pre-processing & Data-analysis values, methods are discussed to discover the cohesion The function of the data pre-processing is and pattern in the selected data and then procedure of acquiring representative data, removing unusual evaluation is appointed [6]. J Global consumption hike and other inconsistencies, defining proper format for time stamping (day, month, hour, a) Data minute) and splitting up the data in identification Real data of electricity consumption is needed and validation sets [2]. The function of the data analysis for estimation and validation purposes of the forecasted is analysing the data to find underlining mechanisms, result. Moreover, to predict the amount of stored energy in the storage devices on day-ahead, the PV generated Author α: Department of Electrical and Electronic Engineering, energy of the corresponding base stations are also University of Asia Pacific (UAP), Bangladesh. needed. As the ultimate goal is to predict the base e-mail: [email protected]

station forecasting, though additional Qualitative a. Normal Energy Consumption Data variables are introduced to recognize the precise pattern On average the yearly consumption of an of the consumption behaviour of each consumer. identical base station in the Netherlands is 3500 kWh.

So, daily electricity consumption on average is 9.5 kWh i. Electricity Use Data Real energy consumption data of different BTS [37]. Consumption profile shown in the figure 2.1 is the on a daily basis at 15 minutes of sampling is used. This electricity consumption pattern of a particular base data will be used to train the network and build the station for the first week of March, 2013 with average forecasted model. Then that forecasted model will be consumption around 9 kWh per day. used to design the PV panel system and schedule the storage device [7]. All the data are taken in Wh and thus

will be forecasted in the same unit. 201 Year

Figure 1: Weekly consumption pattern However, the daily consumption patter in It is very important to identify the non-linearity of ue II Version I ue II Version s different depending on week days and weekend, even the consumption pattern, because forecasting model similar week days does not have similar consumption selection is depend in the degree of non-linearity of the patterns shown in Figure 2. input data. Volume XVII Is

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Figure 2: Daily load consumption

b. Ele ctrical Energy Consumption Compromised with Moreover, this particular base station has installed PV as PV local generation source. So, it is very much

Researches in Engineering After careful analysis, some data are found in understandable this consumption profile is the net the data set which follows a particular pattern but the amount of energy consumed from grid after mitigating of average electricity consumption is less than the some load with PV. Thus, the electricity energy nal standard one. Figure 2.3 shows a consumption profile of consumption data of this type of base stations cannot a day which goes close to zero at mid-day [8]. be used to identify the proper forecasting model. obal Jour Gl

Figure 3: PV Compromised Electricity Consumption

©20 17 Global Journals Inc. (US) Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

Moreover, there are some consumption profile consumption profile of total 3.62 kWh is shown in Figure data sets with very low average daily consumption. A 4. At Figure4

Figure 4: Electricity consumption of some particular equipment

Consumption is very low but at night it goes meters are used as measuring device, thus it has high high. So most probably it is the consumption profile of possibility of missing data and duplicate data. Initially 201 cooling system. Though this consumption profile cannot the full data set is passed through some checking give the proper idea about the consumer load algorithm to identify duplicate data and missing data as Year behaviour. Pre-processing step. However, data with same time 3 ii. Qualitative Variables stamp is treated as duplicate data. For missing data on weekdays, average value of the immediate 7 weekday’s Beside input variables (electrical energy consumption data on the same time sample is taken. consumption), also the qualitative variables are

However missing data for weekend days, average I ersion important for forecasting. Qualitative variables are better consumption of the previous 4 same days on the same known as dummy variables; do not have a natural time sample is calculated. ordering. These variables contain descriptive values, like As an example, to find a missing data on the day of the week. Moreover, all the data are 15 minute ue II V weekdays at y_t it should take the average of previous sampled so hour information is also a qualitative input seven weekdays on the same time t shows in Figure 5. variable. Depending on the time electrical consumption varies like at working days from 9.00AM to 6.00AM consumption should be low and at night when everybody is at home consumption goes high at base

station. However, this hour based consumption pattern Volume XVII Iss also depends on season. Thus, seasonal effect can be

an input variable for forecasting. But this research is () focused on STLF and to capture the consumer behaviour, electricity consumption data of two or three months is used as training data. So most of the case Figure 5: Average value for missing data on weekdays seasonal identification remains same for all training Moreover, to find a missing data on weekend data. Finally, day identification along with our (as an example Saturday) it has to take the average of identification is considered as qualitative input variables previous 4 Saturday of the same time sample shown in for the forecasting model. Figure 2.6. b) Data Pre-processing

Real life data contains huge amount of noise Researches in Engineering and often has quality issues. Such volatility must be

removed before simulation can be performed. If the of nal input values to a forecasting model are poor, it will be our hard to produce a good forecast, irrelevant of the quality of the forecast model. All the steps has to be taken into

consideration before simulation as pre-processing is J Global given below Figure 6: Average value for missing data on weekend • Duplicate data check Filtering unusual and noise from PV generation data set: • Missing data check The PV generated data is also measured in 15- • Filtering unusual and noise from PV generation data minute interval but it is very important to identify the set noise or unusual production. Normally electronics based Duplicate and Missing Data check: measurement devices are used to capture the data from The electricity consumption data of different controller [38]. So, to have unusual production peak or base station of a year is given as Wh/15 min. Smart noise (like production level 1 or 2Wh) is very common.

Moreover, synchronize PV production and consumption by 1,2,3,4,5,6,7 respectively for Monday, Tuesday, data for the same consumer is also important for Wednesday, Thursday, Friday, Saturday and Sunday. scheduling of stage device. Correlation or patterns within the electricity use can aid the forecast if well defined. To discover patterns c) Data Analysis in the electricity use, self-organizing map (SOM) is used

i. Day identification Number as Input of ANN [9]. The motivation behind SOM analysis is to find the It is very important to make some difference pattern of consumption of each day of a week. SOM among the different days of the week so that the models clustering of seven days of a week is shown in Figure can identify the target data set according to the train 2.7. data set. Initially these identification variables are coded into integer value. The days of the week is represented 201 Year

Monday Tuesday Wednesday ue II Version I ue II Version s

Thursday Friday Saturday

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Sunday

Figure 7: SOM clustering of electricity use per day Figure 2.7 illustrates different electricity actual values reaches zero [10]. When considering data consumption pattern of each day. So, as an input of which contain zeros, the metric is undefined. An ANN day identification number will be different for each example of percentage based metric is the MAPE,

Researches in Engineering day. which is one of the most used squire error (MSE). The

of other category is percentage based performance d) Evaluation Method nal indicators, which can be used to compare different data An evaluation method is necessary for three aspects; sets as they are scale independent. To overcome

• Model identification division by zero, a scale free error is proposed by

obal Jour • Performance comparison between models Hyndman and Koehler in 2006 [40]. The above-

Gl • Insight in model performance for practical use mentioned performance indicators are given below. In order to evaluate a forecast made with a In each of the forthcoming definitions is actual value, is the forecasted value, = is specific model, forecast-error metrics or so called 푡 the forecast error and n is the size of the test set. 푦Also, performance indicators are defined. Three types of 푡 푡 푡 푡 y = y is푓 the test mean and = 푒 푦(y− 푓y) performance indicators are discussed. The first used performance indicators are the scale dependent is the1 testn variance. 2 1 n 2 � n ∑t=1 t σ n−1 ∑t=1 t − � metrics. These indicators are on the same scale as the data. One of the most used scaled performance indicator is the mean are extremely large when the

©20 17 Global Journals Inc. (US) Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

i. The Mean Squire Error (MAE) • It is independent of the scale of measurement, but

The mean absolute error is defined as [41] [42] affected by data transformation.

• It does not show the direction of error. 1 MSE = n ( e ) n (a) • MAPE does not panelize extreme deviations. 2 t • In this measure, opposite signed errors do not offset � Its properties are – t=1 each other.

• It measures the average absolute deviation of

forecasted values from original ones. III. Model Building

• It shows the magnitude of overall error, occurred a) ANN based Forecasting Model

due to forecasting. Artificial neural networks (ANNs) constitute a • In MSE, the effects of positive and negative errors class of flexible nonlinear models designed to mimic

are canceled out. biological neural systems of brain. Typically, a biological 201 • For a good forecast, the obtained MSE should be neural system consists of several layers, each with a

as small as possible. large number of neural units (neurons) that can process Year

• Extreme forecast errors are not panelized by MSE. the information in a parallel manner as illustrated in

ii. The Mean Absolute Percentage Error (MAPE) Figure 3.1. Like biological neuron, ANN has also multi- 5 layer structure such that the middle layer is built upon This measure is given by [41] [43] many simple nonlinear functions and able to receive 1 multiple input signals from other neurons. The = | | × 100 % (b) I ersion 푛 procedure of selecting optimal network architectures 푒푡 and their learning approaches are described for 푀퐴푃퐸 � 푡 Its important features푛 are:푡=1 푦 forecasting the wind speed in two different time horizon [11][13]. ue II V • This measure represents the percentage of average

absolute error occurred.

Volume XVII Iss

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Figure 8: Flow of information in biological neuron.

b) Working Principle of Forecasting Model

ANNs are networks typically composed of Researches in Engineering several layers with interconnected elements called neurons. The first or lowest layer is the input layer which gathers external information. The middle or hidden of nal

layers process this information in a fairly elementary our way to produce signals for the connected neurons at output layer. The neurons or nodes at the adjacent layers are usually fully connected by acyclic arcs from a J Global lower layer (input) to a higher layer (output).

Figure 9: A general ANN structure with one hidden layer

Input values are processed by this network to form output values as depicted in a simple non-linear

model, the inputs are independent variables. The functionality estimated by the ANN can be written as: y1, y2,…… ,yn=f (x1,x2,……,xn) Where, x1,x2,……,xn are independent input variables and y1,y2,…… ,yn are dependent output variables. Weights are the key factors of network performance. These weights are continuously updated during the training period to carry out complex nonlinear mapping [12]. In this research the developed forecasting model is trained in supervised way. Once the Figure 11: The taxonomy of ANN architecture

201 network is trained with appropriate training data set, it is ready to perform desire task. Feed-forward neural network (FNN) is fast and

Year simplest ANN because in the case of Multilayer layer network it transmits information form input layer to

6 output layer using some simple structured hidden layer [13]. Normally it maps the static relationship between input and outputs

ue II Version I ue II Version s

Figure 10: Illustration of network weights in supervised learning process c) Network Architecture Complicacy of ANN mainly arises for the hidden Volume XVII Is layers which are used to build the connection between

() inputs and outputs. Thus, it creates an indirect relationship between inputs and outputs. Information received from the input layer is first processed in the hidden layer, and then transmitted to the output layer. Figure 12: Structure of FNN So, the learning capability due to nonlinearity of the through a unidirectional information flow (only input data is mostly depend on number of hidden layers. form input towards output). The inputs are fed directly to A multilayer forecasting model with one hidden layer can the outputs via a series of weights. Each connection perform an arbitrary convex approximation to any may have different weights. Due to lack of any feedback, continuous non-linear mapping. According to the FNN must use a large number of input neurons for universal approximation theorem for neural networks

Researches in Engineering learning the historical data and consequently achieving [49], the standard multilayer feed forward network good results. Despite of being simple, feed-forward of with a single hidden layer and finite number of hidden networks are more efficient in complex nonlinear nal neurons is sufficient for any complex simulate nonlinear forecasting problem with bigger number of input function with any desired accuracy. It concludes with the variables [15]. view that number of hidden layers has an influence

obal Jour according to the complicacy of the problem otherwise e) Mathematical Model

Gl system will be more complicated, even single hidden In a mathematical model, has been developed layer requires large number of nodes. So, it is always a referring to the Figure 3.5 tradeoff of number of hidden layers depending on complicacy of the problem. = + 풒 + 풑 + , d) Selection of the Network 풕 ퟎ 풋 ퟎ풋 풊풋 풕−풊 풕 Depending on the structure of the network ANN 풚 풂 � 풂 품 �휷 � 휷 풚 � 휺 ∀ 풕 풋=ퟏ 풊=ퟏ can be classified in several models. Figure 3.4 shows Her e ( = , , ,….. )are the input and different types of neural networks used for forecasting is the output. The integers are the number of 풚풕−풊 풊 ퟏ ퟐ ퟑ 풑 ( 풚풕 applications. input and hidden nodes respectively. = 풑 풂풏풅 풒 풋 ©20 17 Global Journals Inc. (US) 풂 풋 Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

, , ,…… ) and = ( = , , ,…. . ; = a) Assumptions , , , …… ) are the connection weights and is the The historical data are in Wh and the time 풊풋 ퟏranퟐdomퟑ variable,풒 휷 , 풊are ퟏthퟐe biasퟑ term.풑 풋 Usually, the interval is 15 minutes. As input, total 92 days of previous 풕 ퟏ ퟐ ퟑ 풒 휺 data is taken for pre-processing [14][15].The time range logistic sigmoid functionퟎ ퟎ ( ) = is applied as the 풂 휷 ퟏ is March 1st, 2013 to May 31st 2013. The forecasted nonlinear activation function. Other activation−풙 functions, ퟏ+풆 such as linear, hyperbolic품 tangent,풙 Gaussian, etc. can data represents the consumption for the next day, June 1st 2013. also be used depending upon the use case. The feed forward ANN model in Equation 1 in b) Electricity Consumption Forecasting fact performs a non-linear functional mapping from the i. Model of Feed-Forward ANN past observations of the time series to the future value, Designing a three-layer FNN model for STLF i.ey_t=f (y_(t-1),y_(t-2) 〖,y〗_(t-3),……y_(t-p) ,W)+ ε_t involves several major steps: where Wa vector of all parameters is and f is a function 1) Determine the number of outputs: An FNN model determined by the network structure and connection may have only one output, which can be 201 weights [15] corresponding to the electrical load of a consumer,

Year To estimate the connection weights, non-linear or several outputs, which can represent a 24-hour least square procedures are used, which are based on load profile of several BTSs. Some drawbacks of the 7 the minimization of the error function multiple outputs FNN were discussed in [26].

2) Determine the number of inputs: previous ( ) = = ( ) consumption data of a particular consumer along ퟐ ퟐ 풕 풕 풕 푭 흋 � 풆 � 풚 − 풚� with day identification number is used as target and I ersion Here is the 풕space of풕 all connection weights. input of FNN. The optimization techniques used for minimizing the 3) Determine the number of hidden neurons: It is error function Equation흋 2 are referred as Learning Rules. followed a trial and error method to select an ue II V The best-known learning rule in literature is the back optimal hidden layer structure for used data set at propagation or Generalized Delta Rule. FNN. The number of hidden neuron layer mostly depends on: MAPE, Elapsed Time & Epoch. IV. imulation esults and nalysis S R A The lowest MAPE, lowest time and highest

The optimal structure of ANN is used to forecast Epoch is found for the chosen number of layer. the BTS electricity consumption on day-ahead. In this Observing these parameters, the best output is obtained case 31st of October, 2012 is considered for the from 25 hidden layer amongst different options. Volume XVII Iss demonstration of the model. The imbalance power is

ii. Consumption forecasting on mid-summer (June () calculated by the power deviation between day-ahead 01, 2013) forecaster and 15 minutes ahead forecaster. The flexible Practical consumption data from 30 BTS will be entities are activated in way to reduce this imbalance used to evaluate the forecasting performance of the power. A simple MATLAB-based GUI has been models. In this context, at first it is tried to forecast the implemented to demonstrate how this tool can be user- consumption profile of each consumer on the same day friendly for a customer. with training data set of previous 3 months (92 days).

Table 1: FNN Evaluation

Consumer ANN Researches in Engineering R MSE MAPE (%) of nal 1 0.94285 3.63E+03 33.9695 our 2 0.89787 1.26E+ 04 39.39 3 0.78771 8.70E+03 28.5366

4 0.91719 1.49E+03 52.8844 J Global 5 0.83974 572.452 15.9883 6 0.41161 440.1884 103.0053 7 0.97297 1.27E+03 47.334 8 0.91181 343.6435 25.3231 9 0.9641 1.23E+03 26.5852 10 0.9468 537.9639 27.9004

11 0.8576 4.71E+03 52.6619 12 0.85425 3.95E+03 79.4627 13 0.85881 281.4154 227.0793 14 0.90321 805.5652 40.9806

15 0.9535 1.71E+03 42.787

16 0.90626 1.01E+04 43.5497

17 0.93196 2.39E+03 19.4287

18 0.82326 6.87E+03 20.21 19 0.9188 2.71E+03 46.3432 20 0.94752 9.59E+03 18.249 21 0.94696 914.3805 53.9584

201 22 0.91646 1.04E+04 20.6975 23 0.93604 2.93E+03 40.1062 Year 24 0.95008 1.97E+03 114.3078

8 25 0.85898 5.49E+03 72.9944

26 0.91428 1.92E+03 68.4901

27 0.87358 5.23E+03 28.0127

28 0.93541 2.10E+03 20.6213

29 0.84505 519.5149 626.8921 30 0.88409 1.45E+03 19.0804

ue II Version I ue II Version hours of the day. Considering the case of MAPE, site 5 s a. Forecasting with FNN

Form Table 1, it can be mentioned that FNN has the best output as 15.9883%. Consumer 5 has a performed well. Some out of range data is found in moderate level of error (MSE = 572.452) and a very noticeable regression mismatch as it is far away from 1 MAPE which happened because those consumers had no usage of electricity in their consumer profile at some (R=0.83974)

Volume XVII Is

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Researches in Engineering Figure 13: Forecasting performance of FNN for site 5 of nal obal Jour Gl

Figure 14: MAPE and R of forecasted output of site 5 by FNN In Figure 4.2, the regression function and MAPE and the output. The main reason for this deflection is for for the consumer is shown. The dotted line in the changing the behavior of the consumer at that particular regression represents the exact result and the solid line time. represents the best fit regression line between the input

©20 17 Global Journals Inc. (US) Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

Lest MSE belongs to consumer 8 the output profile almost followed the trend. And most of (MSE=343.6435). But the percentage error is as high as the points are well predicted, though many of them are MAPE=25.3231%. In Figure 6-3 it is clearly visible that lower than the actual data

201 Figure 15: Forecasting performance of FNN for site 8

Year

9 ue II Version I ue II Version s

Figure 16: MAPE and R of forecasted output of site 8 by FNN

Figure 6-4, obtained regression function is one is being consumer 2. For the selected consumer, comparatively good. The mismatched area lies in R=0.8978; MSE=1260; MAPE=39.39. Though the R is between 50 to 100Wh and the MAPE shows a scattered obtained parameters are at moderate level as

pattern of error. Moreover it is clear that the errors largely slightly mismatched from the ideal value, MAPE has Volume XVII Is been obtained in an acceptable range. But the MSE is occurred at the peaks.

Finally, another consideration is done for other so large that can affect the overall performance of the () consumer for optimized evaluation. In this case the forecasting model. overall performance has been considered. The selected Researches in Engineering ournal of ournal obal J

Gl Figure 17: Forecasting performance of FNN for site 2

From the Figure 4.5, the forecasted data is The regression function plotting is lineated matched in almost every point with the actual based on the best points to be found. The most consumption profile. The major mismatch is found at the mismatching is found around 100 to 300Whr. Noticeable higher peaks. Though the forecasted model has percentage errors are found at the peaks from the followed and detected the positions of the peaks well, scattered plotting. but the values estimated are lower than the actual consumption. This mainly happens for the change in the consuming behaviour of the consumer.

Figure 18: MAPE and R of forecasted output of site 2 by FNN c) Scheduling available energy and stored energy is utilized in a

Based on the forecasted model, scheduling of balanced way. During the mid-hour of the day, amount

201 the BTS storage device is designed and operated. For of the available and stored energy is adequate. And the this research two ideal profiles are chosen. For the individual BTS has used the stored energy to meet its Year betterment of the demonstration, the available energy is requirements.

The PV rating, in this case, is 7.5KW. So, the 10 compared with both actual consumption profile and the figure below clears out that, the consumer is using forecasted consumption profile. For the demonstration consumer 2 is chosen. around 400W. That means, he can schedule the storing Figure 4.7 shows the scheduling of a storage device of the device a day ahead to save the rest 7.1KW of with the actual consumption profile. From the figure, energy [16]. sue II Version I II Version sue XVII Is Volume

()

Figure 19: PV production and available energy for site 2

Researches in Engineering Forecasted consumption profile demonstrates the typical scheduling for the device. This is to

nal of nal determine the charging time of the storage device at the day ahead and to be aware of the amount of the energy our to be used. From the figure 4.8, the needed energy for the next day can be estimated. It will be used to obal J

Gl determine the time to store the energy and the dissipating time of the power. And based on the forecasted model, stored energy can be used to make the BTS grid free user. Thus a BTS can be grid independent and produce, store and consume its own energy.

©20 17 Global Journals Inc. (US) Application of Short-Term Load Forecasting for Optimizing the Storage Devices of a Base Station

201

Year

Figure 20: Storage device scheduling using FNN forecasted consumption profile

11 For further evaluation, consumption model of means, this profile will help the consumer to schedule, another consumer is illustrated in Figure 4.9, 4.10 that store and use the energy for its own. demonstrates the same scenario for consumer 17. That ue II Version I ue II Version s Volume XVII Is

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Figure 21: PV production and available energy for site 17 Researches in Engineering ournal of ournal obal J Gl

Figure 22: Storage device scheduling using FNN forecasted consumption profile

V. Conclusion & Future Work Studies in Computational Intelligence, Springer, Vol. 35, pp. 391-418. (Chapter 16). The main focus of this research work was to 7. Long-term electricity demand in China — From identify and justify a optimized forecasting model to quantitative to qualitative growth? Hirschhausen, forecast the electricity consumption at BTS and Christian von and Andres, Michael. 4, April 2000, comparing the results on the basis of the major error Energy Policy, Elsevier, Vol. 28, pp. 231–241. measurement parameters and establishing a reliable 8. Choynowski, Peter. Measuring Willingness to Pay for and most accurate FNN forecasting model. The Electricity. s.l. : Economics and Research forecasted data can be used for designing the Department, Asian Development Bank, July 2002. scheduling and designing the independent power ERD Technical Notes. source for the BTS. This will help the consumer to use its 9. Analysis and evaluation of five short-term load own power to meet its requirement. Thus, it can become forecasting techniques. Moghram, Ibrahim and grid free consumer. Rahman, Saifur. 4, 1989, Power Engineering Review, However, the following recommendations are

201 IEEE Journal and Magazines, Vol. 4, pp. 42-43. suggested for improving the forecaster. 10. Analysis and evaluation of five short term load Instead of using Levenberg -Marquardt Year forecasting techiniques. Moghram, I. and Rahman, algorithm; which is computationally heavy; another

S. 1989, IEEE Transaction s on Power, Vol. 4, pp. 12 learning method called Scaled Conjugate Gradient 1484-1491. (SCG) for bigger ANN approximation and prediction. 11. Application of Neural network Model Combining Larger iteration number of hidden neurons is preferable Information Entropy And Antcolonyclustering Theory for finding optimum solution. In STLF, ARIMA is proved for Short-Term Load Forecasting. Sun, Wei, et al., et as a poor forecaster because of having a significant al. Guangzhou : s.n., 2005. Fourth International level of non-linearity in historical data. However, a hybrid Conference on Machine Learning and Cybernetics. model combined with ANN and ARIMA is needed to be pp. 18-21.

sue II Version I II Version sue investigated. The input variables for the forecasting 12. Electric load forecasting: Literature survey and model should be selected based on partial mutual classification of methods. Nazeeruddin, Hesham K information (PMI) algorithm instead of the last known and Mohammad, Alfares. 2010, International Journal research experience only. This method will detect non- of Systems Science, Vol. 33, pp. 23-34. XVII Is linear dependencies between the input and output as 13. Artificial neural network methodology for short term well as prevent the selection of inputs with redundant load forecasting. Lee, K, Cha, Y and Park, J. 1990, information. It will reduce the dimension of the input Volume NSF Workshop on Artificial Neural Network layer. Aside of using Neural Network Toolbox™ of

Methodology in Power System Engineering,

() MATLAB, better flexibility would be expected. Thus, the Clemson University. user will have more control on every step of the 14. An Adaptive Data Processing System for Weather program. Forecasting. Hu, M J C and Root, H E. 5, 1964, References Références Referencias Journal of Applied Meteorology, Vol. 3, pp. 513-523. 15. Seasonal Time Series Forecasting: A Comparative 1. Short-Term Load Demand Modeling and Study of ARIMA and ANN Models. Kihoro, J.M.,

Forecasting: A Review. Abu-El-Magd, Mohamed A. Otieno, R.O. and Wafula, C. 2, 2004, African Journal and Sinha, Naresh K. 03, 1982, IEEE Transactions of Science and Technology (AJST) Science and on Systems, Man, and Cybernetics, Vol. 12, pp. Engineering Series, Vol. 5, pp. 41-49.

Researches in Engineering 370-382. 16. Performance parameters for grid-connected PV

2. http://www.cs.ccsu.edu/~markov/ccsu_courses/dat systems. Marion, B., et al., et al. 2005, Photovoltaic

amining-3.html Specialists Conference, 2005. Conference Record nal of nal 3. https://ori.hhs.gov/education/products/n_illinois_u/d of the Thirty-first IEEE, pp. 1601 - 1606. our atamanagement/datopic.html 17. Feedforward Versus Recurrent Neural Networks For

4. Forecasting the Demand for Electricity in Saudi Forecasting Monthly Japanese Yen Exchange obal J Arabia. Al-Sahlawi, Mohammed A. 1, 1990, The Rates. Dematos, G., et al., et al. 1, 1996, Financial Gl Energy Journal, Vol. 11, pp. 119-125. Engineering and the Japanese Markets, Vol. 3, pp.

5. Gellings, Clark W. and Barron, Wallace L. Demand 59-75.

Forecasting for Electric Utilities. s.l. : Fairmont 18. Lee, J. Univariate time series modeling and Press, 1992. forecasting (Box-Jenkins Method). s.l. : Econ 413,

6. Short term electric load forecasting: A tutorial. Lecture 04 .

Kyriakides, E. and Polycarpou, M. s.l. : Trends in Neural Computation, Studies in Computational Intelligence, 2007, Trends in Neural Computation,

©20 17 Global Journals Inc. (US) Global Journal of Researches in Engineering: F Electrical and Electronics Engineering Volume 17 Issue 2 Version 1.0 Year 2017 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4596 & Print ISSN: 0975-5861

Design and Construction of a Microcontroller based Smart Solar Charge Controller for Automatic Brightness Controlling of PV based Street Light By Tahmid Hasan Rupam, Farhana Jesmin Tuli, & Md. Habibur Rahman University of Dhaka Abstract- Bangladesh being an over-populated country needs to produce a huge amount of energy to meet its people’s demands. On the other hand, it is quiet impossible to provide the large population with adequate energy with the conventional way of producing energy. Only 62% of our people have the privilege of using electricity. So apart from finding cost effective ways to harness energy, it is required to use the produced energy efficiently. This paper aims to find a way to reduce the pressure on grid energy by empowering the street lights using solar panels. In this regard, it also focuses on having a smart charge controller circuit for ensuring battery longevity. Here PIC16F876A microcontroller has been used to sense different voltage levels and make decisions according to them.. Keywords: solar PV module, PIC microcontroller, LDR sensor, ON/OFF smart solar charge controller, LED street lights, automatic brightness control etc.

GJRE-F Classification: FOR Code: 090605

DesignandConstructionofaMicrocontrollerbasedSmartSolarChargeControllerforAutomaticBrightnessControllingofPVbasedStreetLight

Strictly as per the compliance and regulations of:

© 2017. Tahmid Hasan Rupam, Farhana Jesmin Tuli, & Md. Habibur Rahman. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by- nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Design and Construction of a Microcontroller based Smart Solar Charge Controller for Automatic Brightness Controlling of PV based Street Light

Tahmid Hasan Rupam α, Farhana Jesmin Tuli σ, & Md. Habibur Rahman ρ

Abstract- Bangladesh being an over-populated country needs use of the battery, a charge controller is needed to 201 to produce a huge amount of energy to meet its people’s regulate the flow of current through solar panel to demands. On the other hand, it is quiet impossible to provide battery or through battery to load; which is an essential Year the large population with adequate energy with the

component of a power system, whether the source can conventional way of producing energy. Only 62% of our 13 be PV, wind, hydro, fuel or utility grid[5]. Due to the people have the privilege of using electricity. So apart from finding cost effective ways to harness energy, it is required to urbanization, the number of streets is increasing along use the produced energy efficiently. This paper aims to find a with the street lights. For street lighting, about 10–38% [6] way to reduce the pressure on grid energy by empowering the of the total energy is required around the worldwide . street lights using solar panels. In this regard, it also focuses The LED lights can be used instead of traditional street on having a smart charge controller circuit for ensuring battery lights to save 40-80% electricity than traditional lights[7]. longevity. Here PIC16F876A microcontroller has been used to Manually controlled street lights were susceptible to I ue II Version sense different voltage levels and make decisions according several errors and high power consuming[8} which can to them. The CCP module of the microcontroller has been be impeded by a new method called optical control used for a variable duty cycle PWM signal to adjust the method[9] in which a light sensitive device, such as light brightness of the LED street lights according to necessity. The intensity of the street light will be automatically adjusted and dependent resistor(LDR)is used. will go OFF in the morning. By the use of LED street lights the There have been a lot of studies done regarding reduction of the consumption of energy has been ensured. smart charge controller and automatic brightness olume XVII Iss V Apart from this, the smart solar charge controller can also be controlling of street lights. Sharath Patil G.S et al. (2015) ) used for the electrification of remote places using solar energy designed a PV based automatic street light controlling ( as it is cost effective and easy to implement. system using sensors[1]. Automation of street lights was Keywords: solar PV module, PIC microcontroller, LDR done by LDR sensors. Intensity of led street lights was sensor, ON/OFF smart solar charge controller, LED street controlled by IR sensor and pulse width modulation lights, automatic brightness control etc. according to the vehicle movement. Wallies et al. (2014) developed a solar charge controller by using I. Introduction Microcontroller to protect the battery from deep ajor sources of conventional fossil fuels have discharging and over charging[10]. F.Sani et al. (2014) exhausted to a large scale for its continuous constructed a microcontroller based charge controller to use and these resources can no longer supply charge 12V battery by using 80W solar panel[2]. Vikas M [1] Researches in Engineering energy for 50-60 years from now . To overcome this Khare(2012) demonstrated a model of charge controller situation, solar energy can be used as alternative energy using microcontroller where the battery always charged system which is operated in two different ways - solar at maximum power[3]. Mrs Jaya et al. (2012) presented a [2] photovoltaic system and solar thermal system . The PIC based solar charging controller for battery to store of ournal average increase of photovoltaic production is 48 solar energy and also mentioned how some percent per year since 2002[3] and the price of solar cells disadvantages of analog circuits were solved by this [5] J lobal falls down to 20% for every doubling of industry controller . A.Dawod et al. (2005) designed an G volume[4]. intelligent battery charger based on a control technique To use photovoltaic energy at night, a battery is which was implemented by fuzzy logic[11]. Rohaida required for accumulating solar power. For the efficient Husin et al (2005) proposed an energy efficient microcontroller based automatic street lights (LED) Auhtor α σ: Graduate Student, Department of Electrical and Electronic controller using different types of sensors including laser Engineer ing , University of Dhaka. e-mail: [email protected], [9] e-mail: [email protected] sensor, light sensor and rain sensor . Dr.D Asha et al. Author ρ: Professor, Department of Electrical and Electronic (2012) implemented a system for street lights to use Engineering, University of Dhaka. e-mail: [email protected] solar power efficiently along with an automatic traffic

control unit[6]. Riya et al. (2015) proposed an idea to voltage 15V. This voltage divider circuit is used to sense control the brightness of LED street lights by detecting battery voltage because microcontrollers cannot take the number of vehicles automatically along with a traffic more than 5V as input. monitoring system[7]. In this paper, an idea is proposed for the effective use of solar energy for lighting up the street lights by using energy efficient LED street lights and ensuring the longevity of the battery by involving a charge controller. Solar power is stored in a lead-acid battery and an ON/OFF charge controller is implemented by microcontroller PIC16F876; where this controller reads the sets points of lead-acid battery and controls the battery to be charged fully without

201 overcharging. Here ON/OFF charge controller is used instead of PWM charge controller because the charging Fig. 2: Battery voltage sensing circuit

Year is done by a solar panel. In case of a grid connection, Here, a voltage regulator circuit is needed to

PWM charge controller would be the first choice but for 14 generate constant 5V supply to operate the PV panel, it is not suitable as it produces 20% to 30 % of microcontroller. For this a 7805 IC is used to convert the energy loss in case of a solar panel. In this proposed battery voltage to 5V and its output is fed to the MCLR system, charge controller controls the connection pin along with Vcc pin of the microcontroller to operate between solar panel and battery. The LED light and the microcontroller. battery connection is controlled with the help of microcontroller by sensing light intensity of b) Light Intensity Sensing Circuit surroundings. MiKroC software is used for the logic To control the load (street light) automatically,

sue II Version I II Version sue implementation of the proposed system. light intensity of the environment needs to be sensed. A light dependent resistor (LDR) is used for this purpose. II. BLOCK DIAGRAM OF THE SYSTEM According to the variation of incident light, the resistance of the LDR changes. XVII Is As shown in the following block diagram, the complete system consists of mainly four blocks- Battery Voltage Sensing Circuit, Light Intensity Sensing Circuit, Volume Switching Section and Brightness Control Section along

with the microcontroller working as main controlling unit. ()

Researches in Engineering Fig. 3: Signal Conditioning Circuit A voltage divider circuit is made using a fixed

nal of nal resistor (10k) and an LDR and the output of voltage

our regulator 7805 IC (5V) is used as voltage source. As the light of environment changes, resistance of LDR also

obal J changes and therefore the output voltage of circuit is Fig. 1: Block diagram of the developed system Gl varied. This voltage is sensed by the ADC unit of the The design method of every section of the microcontroller system is described in the following subheadings. c) Switching Section a) Voltage Sensing Circuit After sensing the battery voltage the A Lead acid battery is used in this system and it microcontroller generates an ON or OFF signal through is required to sense the voltage of this battery which is one of its I/O pins based on a predefined algorithm to fed to the microcontroller. To sense the battery voltage, ensure the charging of the battery. When the voltage a voltage divider circuit is used where resistors are level of the battery is lower than the array reconnect chosen in a way that circuit can sense maximum battery voltage, 13.0V(4.33V sensed by the microcontroller) the

©2017 Global Journals Inc. (US) Design and Construction of a Microcontroller based Smart Solar Charge Controller for Automatic Brightness Controlling of PV based Street Light signal generated is ON (or logical 1). The pin is connected to a relay, an electro-mechanical switch to connect the battery with the solar panel. When ON signal is generated the relay turns on and connects the battery with the panel and eventually charging of the battery starts and continues till voltage regulation, 14.4V (4.8Vsensed by the microcontroller) is achieved. Moreover, if the battery voltage falls below 10.8V (3.6V for microcontroller) the load will be disconnected from the battery to prevent it from over discharging. When battery voltage rises to 11.5V (3.83V for microcontroller) then load is again connected to battery. Fig. 5: Brightness Controlling Section

III. SYSTEM SIMULATION 201

The whole system in simulated in proteus is Year

shown in figure 6-

15 ue II Version I ue II Version s

Fig. 4: Switching Section d) Brightness Control Section Pulse width modulation technique is used to control the loads (street light). Pulse Width Modulation, Volume XVII Is

or PWM, is a technique for getting analog results by digital means. Digital control is used to create a square () wave, a signal switched between on (5V) and off (0V).

The duration of "on time" is called the pulse width. To get varying analog values, one can change or modulate that Fig. 6: Schematic diagram of the circuit pulse width. To control the brightness of street light, an In this project, PORTA and PORTC of the analog voltage is sensed by the microcontroller fed from microcontroller are used as input and output port the light intensity sensing circuit. If battery voltage is less respectively. Two pins of PORTA (RA1, RA2) are than 10.8 volts, duty ratio will be 0% (0) i.e. the load is in programmed as ADC module. These RA1 and RA2 pins OFF state. If the light intensity of environment is high are used to sense battery voltages and voltages from enough (greater than 283.3 lux), then load also remains the light intensity circuit, respectively. In these two Researches in Engineering in OFF state. If light intensity of environment varies cases, voltage divider circuit is used as microcontroller between 39.2 to 283.3 lux; PWM provides duty ratio of cannot take more than 5 volts as input. The connection 50%. Below 39.2 lux, load will be lighten up in full of the battery with the solar panel is controlled by relay ournal of ournal brightness, PWM provides duty ratio of 100% (255), load which is connected to the output pin of microcontroller is now in ON state. To drive street light (load), opto- RC0 through transistor C828. Intensity of the street lights coupler and power MOSFET are used as the output of obal J

is controlled by pulse width modulation technique. Gl microcontroller is not enough to lighten up the load. Intensity of load will vary according to light intensity of environment. CCP module is activated for this purpose. The output of CCP1 is connected to optocoupler.

a) Required Calculations b) Flow-chart of the System The flowchart of the system is shown here- Calculations for Battery Voltage Sensing: Table.1: Battery Voltage Sensing:

Charge Battery Voltage Equivalent controller set voltage sensed by decimal points (volts) microcontr number oller (volts)

Voltage 14.4 4.8 982 regulation (VR)

201 Array Reconnect 13 4.33 887 Year Voltage (ARV)

16 Load

Reconnect 11.5 3.866 784 Voltage (LRV)

Low Voltage 10.8 3.6 737 load Disconnect (LVD)

sue II Version I II Version sue

Calculations for LDR voltage sensing:

XVII Is Table. 2: LDR voltage sensing

Light Resistanc Voltage sensed Equivalent Volume intensity e of the by decimal

() LDR(R2)(k microcontroller( number Ω) y)

Low R2>=5.5 Vout>=1.77 >=363

Moderate 1

High R2<=1 Vout<= 0.4545 <=93

Researches in Engineering

nal of nal our

obal J

Gl Fig. 7: Flow-chart of the system

IV. HARDWARE DESIGN AND IMPLEMENTATION For hardware implementation the following components need to be connected according to the Fig. 6. The system was built on a bread board for testing. String of 12V LED lights has been used as street light. the complete hardware of the system is shown in Fig. 7.

Fig. 9: (b)

201 Year

Fig. 8: Complete Hardware of the System 17 a) Programming the Microcontroller Fig. 9: (c) PIC microcontrollers can be programmed in several languages such as MPLab, C, Basic &

FLOWCODE, which are most commonly used languages. But programming in lower level language,

like assembly language, makes the process of I ue II Version programming more complicated. To avoid this problem, s a high level language MikroC has been used. A program written in mikroC compiler includes Hex code, assembly code, header and other files. After writing a program code in C, the hex code is burned into microcontroller memory. For this a software is used named PICkit 2. After burning the hex file into the micro controller using a Volume XVII Is

burner, the whole system was constructed on two bread Fig. 9: (d) boards. The solar panel and the battery were externally () In Fig.9.(a) a piece of paper was used to cover connected to the circuit. the LDR so that night condition could be simulated. As a V. RESULTS AND DISCUSSION result, the battery in charging state (blue LED ON) & load is ON with 100% duty ratio in hardware. And in A number of data were collected on different Fig.9.(b) the same is shown in Simulation. Again in conditions after the hardware of the system was Fig.9.(c) and in Fig.9.(d) 100% duty ratio of PWM signal implemented. Among them some major cases are and the battery voltage(4.40V) and light intensity(1.0lx) mentioned here- reading in simulation is shown respectively. A. Battery in charging state & load is ON with 100% B. Moderate light on LDR, battery is in charging state Researches in Engineering duty ratio and PWM is set with 50% duty cycle ournal of ournal obal J Gl

Fig. 9: (a) Fig.10: (a)

Fig.11: (b) Fig. 1: (b) 201 Year

sue II Version I II Version sue

Fig. 11: (c)

XVII Is In this particular case high artificial light was Fig.10: (c) incident on the LDR. As a result Fig.11.(a) is showing In this case Fig.10.(a) is showing that moderate that the battery is in charging state and the light is off. Volume light is incident on the LDR; battery is in charging This is because the PWM signal is set with 0% duty

state(blue LED) and PWM is set with 50% duty cycle in cycle in hardware. This is shown in Fig.11. (b); 0% duty () hardware. Fig10.(b) shows the 50% duty ratio of PWM cycle of PWM. And in Fig.11.(c) the battery signal and Fig10.(c) illustrates the battery voltage(4.4V) voltage(4.41V) and light intensity reading(963.0lx) in

and light intensity reading(93.0lx) in simulation. simulation circuit is shown.

D. Battery in discharging state and load in ON state C. Battery in charging state and load in 0FF state (0% duty ratio) Researches in Engineering nal of nal our

obal J Gl Fig.12: (a) Fig. 11: (a)

of power is done with efficient use of the generated power i.e. with minimal wastage. Moreover, the charge controller can be used for electrification in the remote areas of Bangladesh using solar energy as it is cost effective. There are still scopes for future works. By proper selection of components based on their availability, the cost can be minimized. However, the only loss occurring in this circuit is due to the MOSFET (0.5 volts). Other than this the proposed system is both cost and energy efficient. In future, if this is implemented commercially, the overall cost can be reduced very significantly.

References Références Referencias 201 1. Sharath Patil G.S, Rudresh S.M, Kallendrachari.K3, M Kiran Kumar, Vani H.V, “Design and Year

Implementation of Automatic Street Light Control 19 Fig. 12: (b) Using Sensors and Solar Panel”, ISSN : 2248-9622, Vol. 5, Issue 6, ( Part - 1) June 2015, pp.97-100 2. Sani, H.NYahya, M. Momoh, I.G. Saidu and D.O. Akpootu, “Design and Construction of Microcontroller Based Charge Controller for Photovoltaic Application”, e-ISSN: 2278-1676,p-

ISSN: 2320-3331, Volume 9, Issue 1 Ver. I (Jan. I ue II Version s 2014), PP 92-97 www.iosrjournals.org 3. Mr.VikasKhare, “Microcontroller Based Solar Charge Controller for Power Application”, International Journal of Electronics Communication and Computer Engineering Volume 3, Issue 1, ISSN 2249 –071X Volume XVII Is 4. https://en.wikipedia.org/wiki/Photovoltaics

5. Mrs Jaya N. Ingole, Mrs Dr. Madhuri A. Choudhary () and Dr. R.D. Kanphade, “PIC BASED SOLAR CHARGING CONTROLLER FOR BATTERY”, Mrs Jaya et al. / International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462

Vol. 4 No.02 February 2012 6. Dr. D. Asha Devi, Ajay Kumar .Y.L, “Design and Fig.12: (c) Implementation of CPLD based Solar Power Saving In this case Fig.12.(a) is showing that Moderate System for Street Lights and Automatic Traffic light in incident on the LDR and the battery is in Controller”, International Journal of Scientific and Researches in Engineering discharging state(Green LED ON) and PWM is set with Research Publications, Volume 2, Issue 11, 50% duty cycle in hardware. In Fig.12.(b) Battery November 2012 1 ISSN 2250-3153 voltage(4.98V) and Light intensity reading(250.0lx) in 7. RiyaRanjan, MeghaGoyal, Bharat kumar, Sandeep simulation. And in Fig.12.(c) the whole system is shown Sharma, “Automatic Vehicle Detecting Street Light of ournal in simulation for this particular case. with Traffic Monitoring System”, IJSRD|| National

Conference on Inspired Learning|| Octorber 2015 obal J

VI. CONCLUSION Gl 8. MUSTAFA SAAD, ABDALHALIM FARIJ, AHAMED In today’s world the demand for energy is SALAH and ABDALROOF ABDALJALIL, “Automatic immense. To account for this ever growing need for Street Light Control System Using Microcontroller”, energy, apart from the development of sustainable ISBN: 978-960-474-339-1 renewable energy sources, emphasis should also be 9. RohaidaHusin, Syed Abdul Mutalib Al given on redesigning systems to use energy more Junid,ZulkifliAbdMajid, Zulkifli Othman, efficiently. In this paper a new model is presented which KhairulKhaiziMdShariff,HadzliHashim, “Automatic will reduce the power consumption of the street lighting Street Lighting System for Energy Efficiency based system compared to conventional design. Here a saving on Low CostMicrocontroller” DOI

10.5013/IJSSST.a.13.01.05 ISSN: 1473-804x online, 1473-8031 print 10. Wallies Thounaojam1, V Ebenezer2, Avinash Balekundri, “Design and Development of Microcontroller Based Solar Charge Controller”, www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 5, May 2014) 11. DAOUD and A. MIDOUN, “Fuzzy Control of a Lead Acid Battery Charger”, JES 2005 on-line : journal.esrgroups.org/jes

201 Year

sue II Version I II Version sue XVII Is Volume

() Researches in Engineering nal of nal our obal J Gl

©2017 Global Journals Inc. (US) Global Journal of Researches in Engineering: F Electrical and Electronics Engineering Volume 17 Issue 2 Version 1.0 Year 2017 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4596 & Print ISSN: 0975-5861

Modelling and Simulation of Microcode based Built-In Self Test Technology for Multiported Memory By Prof. Dr. S. R Patil & Miss. Musle Dipali B. Bharati vidyapeeths college of engg for women pune Abstract- Now a day’s embedded memory area and memory density is increasing. Due to this problem of fault is growing exponentionally.It is necessary to detect and repair those faults. There are different methods to detect the faults present in memory. Asynchronous P-MBIST method is used to detect the faults. Simulation result includes asynchronous P-MBIST which detect mismatch of data occurred and it is shown by high fault pulse. To correct the detected fault redundancy circuit is used. This system is implemented using FPGA platform. Keywords: built-in-self test (MBIST), built-in-self repair (BISR), asynchronous P-MBIST, microcode MBIST multiported memory, redundancy logic array, field programming gate array (FPGA). GJRE-F Classification: FOR Code: 090699

ModellingandSimulationofMicrocodebasedBuiltInSelfTestTechnologyforMultiportedMemory

Strictly as per the compliance and regulations of :

© 2017. Prof. Dr. S. R Patil & Miss. Musle Dipali B. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Modelling and Simulation of Microcode based Built-In Self Test Technology for Multiported Memory

Prof. Dr. S. R Patil α & Miss. Musle Dipali B. σ

Abstract- Now a day’s embedded memory area and memory There are two methods which are efficiently density is increasing. Due to this problem of fault is growing used. These methods are as follow: exponentionally.It is necessary to detect and repair those faults. There are different methods to detect the faults present 1. External Testing: ATPG algorithm is used for external 201 in memory. Asynchronous P-MBIST method is used to detect testing method ATPG algorithm consumes more the faults. Simulation result includes asynchronous P-MBIST area and to test vector generation is time Year which detect mismatch of data occurred and it is shown by consuming. 21 high fault pulse. To correct the detected fault redundancy 2. Internal Testing: BIST scheduling algorithm for circuit is used. This system is implemented using FPGA internal testing it includes LFSR tuning, Test pattern platform. generation. Whereas, BIST and Design for Test Keywords: built-in-self test (MBIST), built-in-self repair (DFT) is on same SOC and overcomes the limitation I ersion (BISR), asynchronous P-MBIST, microcode MBIST of the ATPG algorithm. multiported memory, redundancy logic array, field programming gate array (FPGA). Microcode Asynchronous P-MBIST is implemented and compared with Synchronous P- ue II V I. Introduction MBIST. In Asynchronous M-BIST handshaking signals are used to communication between blocks of test ccording to the ITRS 2015,Now a days the controller. Whereas, in synchronous P-MBIST clocks are memory area is increasing than logic area in used to synchronize the test blocks on SOC. The BIST SOCs.Fig.1[1] shows that shrinking the A having two modes: Normal mode and scan mode The technologies give rise to defect and new fault

power consumption during test mode is more than the Volume XVII Iss models.Thus, the new trends in Multiported memory power consumption during normal mode. Hence to testing will be driven by the following items. choose power efficient BIST method for multiported () BIST: The new fault and new defects eliminate using memory testing. BIST. The only solution that allows at-speed testing for embedded memories, it has generate fault detection II. Related Work and coverage, the higher repair efficiency only detecting Yash Jyothi et al.[1] introduced Asynchronous the faults is no longer sufficient for SOCs so memory P-MBIST method for fault detection and repair of repair is also necessary for this purpose both diagnosis multiported memory. The main advantage is to get and repair algorithm are required. power efficient P-MBIST, it is being proposed to use BISR: Combining BIST with efficient and low cost repair handshaking signals instead of using clock and schemes in order to improve the yield and system implemented on FPGA. Clocks are used to synchronize Researches in Engineering reliability as well. the test blocks on chip and handshaking signals are used to communicate between blocks of test controller. nal of nal Dr. R.K. Sharma et al.[2] introduced Redundancy Array Logic and BISR mechanism used to our low cost repair the fault and to improve the system reliability. Global J Global Bo-Cheng Charles Lai et al.[4] introduced designs of multiported memories that leverage BRAMs have been proposed to attain better utilization of FPGA resources as well as system performance. BRAMs in an Fig.1 : Embedded Memories in Future SOCs [1] FPGA can support two access ports that can be used as either a read or a write port. Auhtor α σ: Department of Electronics and telecommunication Bharati Vidyapeeth’s College of Engineering for Women Pune, 43 Savitribai Phule Pune University. e-mails: [email protected], [email protected]

III. built-in self test (bist) Memory Built-In Self Test is test circuitry used to test on-chip memory devices. It contains finite state machine to generate test vectors to test vectors to test memory during test mode. Test coller includes Address, Data, read/write control. This address, data and read/write control signal is given as input to comparator and multiplexer. Multiplexer uses two modes of

operations: Normal mode-In normal mode memory acts as a normal memory. Test Mode-During test mode test Fig. 3: Block Diagram of Asynchronous P-MBIST [1] coller provides data and address to memory for testing The control circuitry contain following blocks: purpose. In test mode while performing read operation Microcode Instruction storage unit, Test collar, data from test coller and output of memory are given to

201 comparator, Clock Generator. The Test Collar circuitry comparator for fault detection. Then, comparator consists of Address Generator, RW Control and Data compares test vectors with memory output. If, memory Year Control. Common Clock is used for Synchronous is working properly then, No Fault is detected and it is MBIST. In Microcode Instruction Storage (MIS), 4

22 declared as memory is fault free but, if fault pulse instruction operations are stored that are R0, R1, W0, becomes high it shows that memory under test is faulty. W1 as shown in Table I. [1] Address Table No.1: Microcode Instruction [1] R/W Data signal ue II Version I ue II Version s MBIST Controller

Input MUX V. Flowchart of Asynchronous p-mbist The flow of asynchronous P-MBIST is as shown

Volume XVII Is in fig .4, fig. 5 and fig. 6. It follows the following steps:

i. If there is request from Microcode Instruction () Multiported Storage (MIS) to Pulse generator (PG), then PG Redundancy circuit Memory sends Start Pulse to MIS to start the asynchronous operation. In next step MIS checks for request from Test Collar (TC), if so it sends microcode instructions to TC. TC then sends the acknowledgement signal to pulse generator indicates that TC is getting instructions from MIs. Output MUX ii. Output of TC Data which includes test address, corresponding data and R/W control signals send to

Researches in Engineering input multiplexer (MUX) if MUX sends high pulse of

of Data Out request. Multiplexer is originally not a multiplexer but

nal concept used for this block is according to working Fig. 2: Structure of P-MBIST of normal multiplexer. Here mode signal is select IV. Implementation of Asynchronous line for MUX. iii. If mode=1then PMBIST works in test mode then it obal Jour p-mbist

Gl selects TC data. If mode=0 then it is in normal The block diagram shown in Fig.3 [1] the mode, during this mode test circuitry is in ideal asynchronous P-MBIST contains handshaking signals condition and memory works as normal memory instead of using clock. Request and acknowledge without under test and sends output of external signals perform communication in Asynchronous P- Address, corresponding data and R/W control MBIST. signal. When MUX is under test mode then it sends TC data to memory if request signal is high from memory to MUX.

201 Year

Fig. 6: Flowchart Step-III I ersion VI. Comparator compares inputs provided by TC and

memory output data during test mode and gives ue II V Fig. 4: Flowchart Step-I high fault pulse if any mismatch happens between these inputs

V. Asynchronous p-mbist Simulation The simulation of asynchronous P-MBIST is

depending upon request signal and mode. Output Volume XVII Iss Response: Normal Mode: When mode=0, MUX selects

normal mode, then test controller is off so as () comparator is off. At this moment memory acts as normal memory without under test and generates external address and data if rw=0(i.e. reads address and corresponding data).During this mode as comparator is off, no fault pulse is generated. In this mode, memoutdata (memory output) data is data (External data) provided for normal memory operation. Test Mode: If mode=1, Memory is under test. If req=1, microcode instruction storage generates Read/Write Researches in Engineering control for test collar. Test collar writes data if tcrw=0 otherwise read to memory through MUX. The data from test collar and output of memory is compared in of nal

comparator. If mismatch happens at output of our comparator, comparator generates fault pulse=1 otherwise fault pulse=0[1]. Global J Global VI. Repair Module Fig. 5: Flowchart Step-II Fig.8.Shows the Repair Module including the redundancy array and output multiplexer and its interfacing with the existing BIST module. Fig.7 An array of redundant words placed in parallel with the memory. The following interface signals are taken from the MBIST logic:1) A fault pulse indicating a faulty location address,2) Fault address,3)

Correct data that is compared with the results of Memory under test. The MBISR logic used here can function in two modes. a) Mode 1: Test & Repair Mode In this mode the input multiplexer connects test collar input for memory under test as generated by the BIST controller circuitry. As faulty memory locations are detected by the fault diagnosis module of BIST Controller, the redundancy array is programmed. A redundancy word is as shown in Figure. 7 The fault pulse acts as an activation signal for programming the array. The redundancy word is divided into three fields. The FA (fault asserted) indicates that a fault has been 201 detected. The address field of a word contains the faulty address, whereas the data field is programmed to Year contain the correct data which is compared with the

24 memory output. The IE and OE signals respectively act Fig. 8: Redundancy Array Logic [2]

as control signals for writing into and reading from the Fig.8.Shows the simulated waveform of fault data field of the redundant word. diagnosis module, magnified at seventh pulse to indicate how signals like ‘fault pulse ’, ‘faulty location addresses and ‘correct data’ are generated by this module for successful interfacing with the Redundancy Array logic.[2]

VII. Results 1. Single port Memory The single port memory support single read and XVII Issue II Version I II Version XVII Issue write operation. olume V )

(

Fig. 7: Redundancy Word Line [2]

b) Mode 2: Normal Mode Fig.9: Result of Single port Memory During the normal mode each incoming address is compared with the address field of 2. Dual port Memory programmed redundant words. If there is a match, the The single port memory support dual read and Researches in Engineering data field of the redundant word is used along with the write operation. faulty memory location for reading and writing data. The output multiplexer of Redundant Array Logic then

ournal of ournal ensures that in case of a match, the redundant word data field is selected over the data read out ( = 0) of the obal J

l faulty location in case of a read signal. This can be G easily understood by the redundancy word detail shown in Figure 7.

Fig.10: Result of Dual port Memory

3. Multiported Memory VIII. Conclusion It requires significant amount of BRAMs to implement a memory module that supports multiple In simulation results of different types memories read and write ports. where implemented. The efficient BRAM-based multiported memory designs on FPGAs. The existing

design methods require significant amounts of BRAMs to implement a memory module that supports multiple read and write ports. In simulation results of different methodology of P-MBIST where implemented. To synchronize the blocks synchronous PMBIST uses clock due to this it consume more power because of excessive switching activity and to communicate between the blocks of MBIST asynchronous MBIST uses handshaking signals and it consume less power. The 201 Fig. 11: Result of Multiported Memory word redundancy uses spare words in place of spare

rows and columns. It stores faulty location address Year

4. Synchronous P-MBIST immediately supporting on-the-fly fault repair memory.

25 References Références Referencias 1. HassenMestiri, FatmaKahri BelgacemBouallegue, Mohsen Machhout, “A high speed AES design resistant to fault injection attacks”, Microprocessors and Microsystems journal,2016 Elsevier, pp.47-55 2. Dr. R.K. Sharma Aditi Sood, “Modeling and Simulation of Multi-Operation Microcode based I II Version sue

Built-In Self Test for Memory Fault Detection and Fig.12: Simulation Result of Synchronous P-MBIST Repair”, IEEE Annual Symposium on VLSI, 2010 3. Prof.Vinod Kapse, Mohammed Arif, “Optimization of 5. Asynchronous P-MBIST Microcode Built-In Self Test By Enhanced Faults Coverage for Embedded Memory”, IEEE Students’ olume XVII Is

Conference on Electrical, Electronics and Computer V )

Science, 2012. 4. Bo-Cheng Charles Lai, Member, IEEE, and Jiun- ( Liang Lin,”Efficient Designs of Multiported Memory on FPGA”,ieee transactions on very large scale integration (vlsi) systems,2016. 5. G. A. Malazgirt, H. E. Yantir, A. Yurdakul, and S. Niar,“Application specific multi-port memorycustomization in FPGAs,” in Proc. IEEE Fig.13: Simulation Result of Asynchronous P-MBIST Int.Conf. Field Program. Logic Appl. (FPL), Sep. 2014, pp. 1–4. 6. Redundancy Array Logic 6. Sandra Irobi Zaid Al-Ars Said Hamdioui.Memory Researches in Engineering Test Optimizationfor Parasitic Bit LineCoupling in SRAMs. IEEE International Test Conference, 2010. 7. N. Z. Haron, S.A.M. Junos, A.S.A. Aziz, “Modelling and Simulation of Microcode Built-In Self test Architecture for Embedded Memories”, In Proc. of obal Journal of obal Journal IEEE International Symposium on Communications l G and Information Technologies pp. 136-139, 2007. 8. S. Hamdioui, G.N. Gaydadjiev, A.J .van de Goor, “State-of-art and Future Trends in Testing Embedded Memories”, International Workshop on Fig.14: Simulation Result of Redundancy Logic Array Memory Technology, Design and Testing (MTDT’04),2004. 9. P. Bernardi, M. Grosso, M. S. Reorda, and Y. Zhang, "A programmable BIST for DRAM testing

and diagnosis," in Test Conference (ITC), 2010 IEEE International, 2010, pp. 1-10. 10. C. E. LaForest and J. G. Steffan, “Efficient multiported memories for FPGAs,”inProc. 18th Annu. ACM/SIGDA Int. Symp. Field Program.Gate Arrays, 2010, pp. 41–50. 11. Xilinx. 7 Series FPGAs Configurable Logic Block User Guide,accessed on May 30, 2016. [Online].Available:http://www.xilinx.com/support/doc umentation/user_guides/ug474_7Series_CLB.pdf. 12. C. E. LaForest, M. G. Liu, E. Rapati, and J. G. Steffan, “Multi-ported memories for FPGAs via XOR,” in Proc. 20th Annu. ACM/SIGDA Int. Symp.

201 Field Program. Gate Arrays (FPGA), 2012, pp. 209– 218. Year

XVII Issue II Version I II Version XVII Issue olume V )

( Researches in Engineering ournal of ournal obal J l G

©2017 Global Journals Inc. (US) Global Journal of Researches in Engineering: F Electrical and Electronics Engineering Volume 17 Issue 2 Version 1.0 Year 2017 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4596 & Print ISSN: 0975-5861

Modeling and Mitigation on Conducted Emission for Switch Mode Power Supply Li Lin, Qiu Dongmei , Yan Wei & Gao Xiang Nanjing Normal University Abstract- The switch mode power supply (SMPS) have been widely used in the electrical and electronics systems for AC-DC and DC-DC power conversion, which can generate a lot of electromagnetic interference (EMI), especially conducted emission (CE) from 9kHz to 30MHz. The traditional CE models and mechanisms have been present for three line systems, including live, neutral and ground lines, while a novel CE models and mechanisms have been proposed in the paper for two line SMPS. And the voltage division factor, isolation factor and impedance under SMPS side of artificial mains network have been studied based on high frequency parasitic parameters to analyze the CE measurement uncertainty. Moreover, three methods have been designed to reduce the CE of SMPS, such as the capacitor shunt between the source and drain electrodes of MOSFET, CM choke and crosstalk choke, and the capacitors matrix. Keywords: electromagnetic interference (EMI); noise mechanism; noise mitigation; SMPS; conducted emission.

GJRE-F Classification: FOR Code: 290901

ModelingandMitigationonConductedEmissionforSwitchModePowerSupply

Strictly as per the compliance and regulations of :

© 2017. Li Lin, Qiu Dongmei , Yan Wei & Gao Xiang. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Modeling and Mitigation on Conducted Emission for Switch Mode Power Supply

Li Lin α, Qiu Dongmei α , Yan Wei σ & Gao Xiang ρ

Abstract- The switch mode power supply (SMPS) have been through the parasitic capacitor between the primary and widely used in the electrical and electronics systems for AC-DC secondary coils [12]. To improve the topology of network, and DC-DC power conversion, which can generate a lot of the network was designed with one radio frequency electromagnetic interference (EMI), especially conducted transformer with 2:1 by Mardiguian [13]. Moreover, the 0° emission (CE) from 9kHz to 30MHz. The traditional CE models and 180° power dividers have been used to constitute the

and mechanisms have been present for three line systems, 201 including live, neutral and ground lines, while a novel CE models noise separation network [14]. Based on the above models and mechanism, a and mechanisms have been proposed in the paper for two line Year

lot of categories have been carried out to reduce the CE

SMPS. And the voltage division factor, isolation factor and impedance under SMPS side of artificial mains network have noises [15-19]. The EMI noises from DC-DC Buck 27 been studied based on high frequency parasitic parameters to conversion has been suppressed by employed MOSFET, analyze the CE measurement uncertainty. Moreover, three decoupling capacitors and optimal design for PCB [15]. methods have been designed to reduce the CE of SMPS, such A frequency modulated (FM) source of conducted as the capacitor shunt between the source and drain electrodes emission has an adverse effect on a DC power system of MOSFET, CM choke and crosstalk choke, and the capacitors and spread spectrum modulation is proposed to reduce matrix. The experiment results show that the CE of the power concentrator and colonoscopy can be suppressed well and EMI noises [16]. The Power Integrity problem for high pass EN 55022 class B, thus realize the proposed approaches speed systems is discussed in context of selection and I ue II Version good validation. placement of decoupling capacitors. The optimal Keywords: electromagnetic interference (EMI); noise capacitors and their locations on the board are found mechanism; noise mitigation; SMPS; conducted emission. using the presented methodology, which can be used for similar power delivery networks in high speed systems I. INTRODUCTION [17]. A modified LLCL-filter topology is proposed to provide enough attenuation on the conducted EMI noise olume XVII Iss witch mode power supply (SMPS) has been widely V

as well as to reduce the DC side leakage current [18]. A )

applied in the electrical and electronics devices, S which can realize the AC-DC, DC-DC conversion new method to reduce CM EMI at the DC input of ( and generate larger amount of electromagnetic variable-speed motor drives is analyzed. Unlike interference (EMI), especially conducted emission (CE) conventional passive or active filtering techniques that from 9kHz and 30MHz [1-5]. The CE standards have rely on impedance mismatch or active noise cancellation, been established by the most countries and areas, such the method uses a passive circuit with matched as EN 55022 [6]. impedance to cancel the inverter CM current [19]. In recent years, the CE models and mechanisms However, the above noise reduction methods can’t obtain for live, neutral and ground lines system have been the EMI source and solve the EMI problem fundamentally proposed to analyze the noises paths, which contributes in the economy and practical scale. In view of above analysis and on basis of the to noise suppression [7-11]. The CE models consist of Researches in Engineering common mode (CM) and differential mode (DM) noises. acquired achievements about EMC of electronic The CM noise path is from live/neutral line to ground line, equipments, the CE models and mechanisms for SMPS and the DM path is from live line to neutral line. Four kinds have been analyzed in the paper. And the CE of noise separation networks have been proposed to measurement uncertainty was studies based on the of ournal determine the CE mechanism by extracting CM and DM voltage division factor, isolation factor and impedance

under SMPS side of artificial mains network. Then, three J lobal noises by Paul, See, Mardiguian and Guo [2, 12-14]. Paul network is composed of two radio frequency transformers methods have been proposed to reduce the CE, such as G with 1:1 and artificial switch, through which the high the capacitor shunt between the source and drain frequency (HF) noises are generated and coupled [2]. electrodes of MOSFET, CM choke and crosstalk choke, The core of See network is also two radio frequency and the capacitors matrix. The experiment results show transformers with 2:1, but the HF noises are generated that the CE noises of the power concentrator and colonoscopy can be suppressed effectively and Auhtor α: Jiangsu Institute of Metrology, Nanjing, 210023, China. efficiently by using the present approaches, while can Auhtor σ: School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210042, China. e-mail: [email protected] pass the EN 55022 and improve the safety and EMI

Corresponding Author ρ: [email protected]. performance.

II. SMPS OPERATION DESCRIPTION Due to the difference between the topology of SMPS (two line system without ground line) and SMPS can support direct current (DC) power to traditional three line system, the conducted emission the load through four diodes and metal oxide mechanism will be studied. semiconductor field effect transistor (MOSFET). Voltage dependent resistance (VDR) was employed to resist and III. UNCERTAINTY OF CONDUCTED EMISSION suppress the external surges and interferences. Three MEASUREMENT capacitors and common mode (CM) choke were used to reduce the high frequency (HF) EMI noises. However, According to EN 55022 and FCC Part 15, a large amount of EMI noises were generated by SMPS conducted emission can be detected by EMI receiver via four diodes and FET, which will go to power supply and artificial mains network (AMN), where quasi peak through power line and influence other electrical and detector and average detector should be fixed on the electronics devices. EMI receiver. CM and differential mode (DM) models were To analyze the uncertainty of CE measurement, 201 established to analyze the noise mechanism and the topology structure and HF parasitic parameters of AMN will be investigated. According to CISPR 16, the Year suppress the above EMI noises based on three line system including live, neutral and ground lines, as topology structure is shown in Fig.2, where C1 is 1μF, C2

28 is 0.1μF, R1 is 50Ω, R2 is 1kΩ and L1 is 50μH. The HF

shown in Fig.1. noise from 9kHz to 30MHz in power supply can be L reduced by capacitor C1 and inductance L1, and the 50Hz current is also ordinary and functional. The CE from 9kHz to 30MHz in SMPS can be extracted through capacitor C . Resistance R is used to bypass flow and Power DM Noise 2 1 N SMPS resistance R is designed to measure CE. Supply 2

sue II Version I II Version sue

CM Noise G XVII Is Fig. 1: CM and DM noise mechanism based on three line system Volume

Cesl1

() AMN L L

Res Les L1

Lesc2 C1 Cesl1

C N 2 N L L1 S Res es M Lesc2 Power P Lesc1 Lesc1 supply

S C2

Researches in Engineering R2 R1 C1

R2 R1 nal of nal G G our

obal J Fig. 2: Topology structure of AMN based on CISPR 16 (red characters are HF parasitic parameters)

Gl Considering the HF parasitic parameters of the To analyze the characteristic of AMN, the above capacitors, inductances and resistances, as voltage division factor, isolation factor and impedance

shown in Fig.2, Lesc1 and Lesc2 are the parasitic under SMPS side were defined as

inductance of C1 and C2, respectively. Cesl1 is the U U parasitic capacitor of L1. Les and Res are the parasitic VIF ==20log L VIF 20log N inductance and resistance of the interface adapter. In LNUU LG NG (1) the paper, Res is neglected due to the adapter design U L U N and manufacturing technique. IRRLN==20log IRR 20log UUPLG PNG

Where, VIFL and VIFN denote the live and neutral c) The impedance under SMPS side of AMN lines voltage division factor of AMN, IRRL and IRRN To determine the impedance under SMPS side represent the live and neutral lines isolation factor of of AMN, Les was considered as 10nH and 100nH, AMN, UL and UN express the total CE of live and neutral respectively, and the other parasitic parameters can be lines, ULG and UNG express the HF EMI noise between neglected due to the measurement circuit, as shown live/ neutral and ground lines. inFig.5. a) The voltage division factor of AMN 60 To analyze the voltage division factor of AMN, the above parasitic parameters were considered lonely as 55 shown in Tab.1 and the results were shown in Fig.3. Table.1: Four Parasitic Parameters Assumption 50

Lesc1 1 nH 45 Ideal 201 Lesc2 0.1 nH

L =10 nH Year Cesl1 40 pF es 40

Les 100 nH

Impedance under SMPS side/ Ω Les=100 nH 29 2 35 0 5 10 15 20 25 30 Ideal Frequency/MHz Lesc1 Lesc2 Fig.5: The impedance under SMPS side of AMN Cesl1 Les considering HF parasitic parameters / dB L 0 As shown in Fig.5, with the Les and VDF ue II Version I ue II Version measurement frequency increasing, the impedance s under SMPS side was increasing greatly. Therefore, the proper AMN should be designed

-2 and employed to determine the CE and decrease the 0 5 10 15 20 25 30 Frequency/MHz uncertainty of CE measurement through capacitor and inductance matching. Fig. 3: The voltage division factor of AMN considering Volume XVII Is HF parasitic parameters IV. CE CHARACTERISTIC MECHANISM MODEL

As shown in Fig.3, Lesc2 and Les have great a) CM and DM models () influence on the voltage division factor of AMN. Due to the difference between the two line b) The isolation factor of AMN SMPS system and three line system, the CE To analyze the isolation factor of AMN, the above characteristic mechanism model should be established. parasitic parameters were considered lonely as shown Considered that SMPS have live and neutral lines but no in Tab.I and the results were shown in Fig.4, where the ground line, the CM and DM noise transmission loop can’t be formed and realized. Les can be neglected due to the measurement circuit. As shown in Fig.2, the two different results can 0 be obtained based on EN 55022, as follows: Researches in Engineering

IIIIL= NL≠ N

Where, IL and IN denote the total CE current / dB

L -60 through live and neutral lines. Based on the formula (2), of ournal Ideal L the unbalanced noise current can be defined as

VDF esc1

Lesc2

IIL−= DM IN + IDM (3) obal J Cesl1 Gl Where, IDM represents the unbalanced noise current and can be considered as DM noise current. -120 0 5 10 15 20 25 30 Then, Frequency/MHz

Fig.4: The isolation factor of AMN considering HF ICM = IIL − DM  (4) parasitic parameters ICM=II N + DM

As shown in Fig.4, Cesl1 have great influence on Where, ICM signifies the balanced noise current the isolation factor of AMN. and can be considered as CM noise current.

Based on Fig.2, the total live line noise have two L bypass loops, such as live to ground noise I and live LG U UDM 50 Ω DM to neutral noise ILN. Similarly, the total neutral line noise 100 Ω also have two bypass loops, such as neutral to ground N

noise ING and neutral to live noise INL. Supposed that ZDM ZDM II= + I 50 Ω L LG LN (5) = + IIN NGI NL Moreover, the amplitude of the I and I were LN NL (a). CM noises (b). DM noises equal but the phases were opposite. Fig. 6: Noise equivalent transmission circuits IINL= − LN (6) b) CE model for SMPS By substituted to formula (5), it can be obtained Due to the two lines system, the parasitic

201 capacitor to ground can be considered to analyze the II=+=− I III (7) L LG LN N NG LN equivalent bypass circuits of CM and DM noises, as

Year and, shown in Fig.7.

The DM noise path was from live line to neutral 30 =−=+ (8) ILG II L LN INGII N LN line, the same as the three line system, as shown in Fig.1. However, the CM noise path was from live/neutral Considered ILN as IDM, line to ground line, then to the SMPS through the

ICM =−=−= IIL DM IIL LN ILG parasitic capacitor CPG.  (9) Therefore, CE for SMPS still have CM and DM ICM =+=+= IIN DM IIN LN I NG noises, but not the only DM noise, where noise Based on the formula (3) and (9), the CM noise can be suppression categories should be designed not only for sue II Version I II Version sue defined as DM noise but also for CM noise. Moreover, the DM noise is much larger than CM + UULN noise in general because the parasitic capacitor is little, UUCM= LG =UUNG CM = (10) 2 even ignored. XVII Is

The equivalent transmission circuit of CM noise L was shown in Fig.6(a). Volume Where, UCM and ZCM represent the equivalent

CM noise source and its impedance. () SMPS Based on the formula (3) and (8), the DM noise Power DM Noise N can be defined as Supply II−− UU = LN = LN (11) CM Noise IUDM DM CPG 22 G

The equivalent transmission circuit of DM noise Fig. 7: CE model for SMPS was shown in Fig.6(b). Where, UDM and ZDM represent the equivalent V. CE MITIGATION METHOD FOR SMPS DM noise source and its impedance. Researches in Engineering a) The capacitor shunt between the source and drain Moreover, ZCM and ZDM can be determined by employing the insertion method, dual current probe electrodes of MOSFET nal of nal method, single current probe current, scattering The switch frequency can be controlled through

our parameter method and the proposed dual resistance the grid electrode of MOSFET and the HF noise will calibration method. generate and couple to the source and drain electrodes

obal J due to the MOSFET. The frequency of noises are based L N Gl on the switch velocity, basically from 9kHz to 30MHz, which is the CE source. UCM UCM The capacitor shunt between the source and 25 Ω 50 Ω 50 Ω drain electrodes can be used to reduce the above HF

ZCM ZCM noises. Moreover, the value of the capacitor should be smaller than 0.1μF not only for the noise mitigation but also for the safety regulations & design, as shown in

Fig.8, where, C4 denotes the capacitor shunt between the source and drain electrodes of MOSFET.

L2 D5 LC1 D1 D2 Power CM1 CM2 M C4 C3 Load Supply VDR

D3 D4

Fig. 8: Topology structure of SMPS

The crosstalk choke whose live and neutral lines b) CM choke and crosstalk choke 201 The CM choke can be employed to suppress are in the different orientation, can be used to solve the the CM noises, but can’t solve the environmental above problem. With different of CM choke, the crosstalk choke can be considered as the magnetic Year

electromagnetic field coupling. As shown in Fig.9(a), the

live and neutral lines are in the same direction in the CM dipole, which can also obtain the environmental 31 choke, which can well reduce the CM noise due to the electromagnetic field. And the magnitude of the electromagnetic field offset. Meanwhile, the CM choke coupling noise resolves the area of dipole and the noise can be considered as two electric dipoles which can frequency. As shown in Fig.9(b), the area of the dipole is receive the environmental electromagnetic field greatly the area between the live and neutral lines, which is very and couple to the power lines. And the amplitude of the little. As shown in Fig.12, the LC1 represents the CM coupling noise is based on the length of dipoles and the choke and crosstalk choke. ue II Version I ue II Version noise frequency. s LN N L LN N L

CM choke Crosstalk choke Volume XVII Is

()

(a). CM choke (b). Crosstalk choke Fig. 9: CM choke and crosstalk choke c) The capacitors matrix VI. EXPERIMENT VERIFICATION The single capacitor with the fixed value can suppress the certain spectrum noise due to HF parasitic To verify the proposed methods, the SMPSs of parameter of the capacitor, such as the parasitic the power concentrator and colonoscopy are studied in Researches in Engineering inductance of the pins. The capacitors matrix can be the paper. In the experiment, R&S EMI receiver ESL3 employed to solve the problem, which consists of and R&S artificial mains network (AMN) ENV216 are used to determine the CE generated by the above 100pF, 1nF, 10nF, 0.01μF and 0.1μF. The different

devices. of ournal frequency noise will be reduced by the capacitors with different values, as shown in Tab.2. As shown in Fig.8, a) SMPS of the power concentrator

obal J the CM1 and CM2 denote the two capacitors matrix. The original CE result of the power concentrator Gl Tab. 2: Noise Mitigation Based on Different Capacitors is shown in Fig.10(a),(b). According to EN 55022 Class B, the noise can’t pass the standard from 150kHz to Capacitor’s Value Reduced noises frequency 10MHz. The average noises are 54dBμ[email protected] 100pF 20MHz and the above and 55dBμ[email protected]. And it exceeds 20dBμV from 1nF 10MHz-30MHz 3MHz to 5MHz, even critical.

10nF 5MHz-20MHz Based on the proposed method, the mitigation

0.01μF 500kHz-10MHz approaches are designed as follows:

0.1μF 9kHz-1MHz

1. EMI filter for SMPS of the power concentrator is

designed, as shown in Fig.10(c), where L1 denotes 10mH CM choke, both L2 and L3 represent 1mH inductance, C1, C2 and C3 signify 0.01μF, 10nF and 1nF, respectively. 2. 10nF capacitor is shunt between the power supply of the carrier module to HF noises. Due to the above methods, the CE of the power concentrator can pass EN 55022 Class B, where the average noises are 35dBμ[email protected] and 41dBμ[email protected]. And the safety margin of the power (a). The power concentrator concentrator can reach 10dBμV, as shown in Fig.10(d).

100 201

80 Year EN 55022B_QP 60

EN 55022B_AV 32 40 CE / dB μ V

0 0.15 1.00 10.00 30.00 Frequency / MHz (b). The original CE result sue II Version I II Version sue

L1 L2 XVII Is C1 C2 C3

L3 Volume

() (c). EMI filter for the SMPS of the colonoscopy

100

EN 55022B_QP 60 EN 55022B_AV

40 CE/ dB μ V

Researches in Engineering 0 0.15 1.00 Frequency / MHz 10.00 30.00

nal of nal (d). The final CE result based on the proposed method

our Fig.10: CE experiment of SMPS for the power concentrator

obal J b) SMPS of the colonoscopy Gl The original CE result of the colonoscopy is

shown in Fig.11(a),(b), and the noise can’t pass EN

55022 Class B, as shown in Tab.3.

Tab. 3: The Original CE of the colonoscopy

Freuqency/MHz Average/dBμV Exceed/dBμV 0.16 66.42 1.42 0.18 67.02 3.02 0.22 68.01 5.03 0.24 65.01 3.01 0.26 65.02 4.11 0.30 64.96 5.04 0.32 65.04 6.16 0.34 63.95 5.82 Based on the present approach, the conversion chip, where the inductance is 1.2μH and suppression methods are designed as follows: the capacitor is 0.15μF. 201 1. T model EMI filter is designed for SMPS of the Due to the above methods, the CE of the

colonoscopy, as shown in Fig.11(c), where L1 and L2 colonoscopy can pass EN 55022 Class B, where the Year

denote 35μH and 1.36μH crosstalk chokes, average noises are shown in Tab.4. And the safety respectively, C represents 0.022μF capacitor. margin of the colonoscopy can also reach 10dBμV, as 33 2. L model EMI filter is also designed for the DC power shown in Fig.11(d). Tab. 4: The Final CE of the colonoscopy

Freuqency/MHz Average/dBμV Decline/dBμV

0.16 50.20 16.22

0.18 49.96 17.06 I ue II Version s 0.22 42.62 25.39

0.24 44.88 20.13

0.26 42.16 22.86

0.30 39.92 25.04

0.32 43.81 21.23

0.34 40.68 23.27 Volume XVII Is

() Researches in Engineering

(a). The power concentrator ournal of ournal 100

80 obal J

EN 55022B_QP Gl 60 EN 55022B_AV

40 CE / dB μ V

0 0.15 1.00 10.00 30.00 Frequency/ MHz (b). The original CE result

017 Global Journals Inc. (US) Modeling and Mitigation on Conducted Emission for Switch Mode Power Supply

Ｌ L1 L2

Ｎ

(c). EMI filter for the SMPS of the colonoscopy

100 201 80

Year EN 55022B_QP 60 EN 55022B_AV

34 40 CE / dB μ V

0 0.15 1.00 Frequency/ MHz 10.00 30.00 (d). The final CE result based on the proposed method

sue II Version I II Version sue Fig.11: CE experiment of SMPS for the colonoscopy

VII. CONCLUSION REFERENCES RÉFÉRENCES REFERENCIAS XVII Is In this paper, CE mechanism generated from 1. Clayton R. Paul, Introduction to Electromagnetic the special two line SMPS is analyzed to solve the safety Compatibility (Second Edition), Hoboken, U.S.A:

Volume and EMI problem of SMPS. Following conclusions are John Wiley & Sons, Inc, (2006), 326-343.

obtained. 2. Henry W. Ott, Electromagnetic Compatibility () 1) The voltage division factor, isolation factor and Engineering, Hoboken, U.S.A: John Wiley & Sons, impedance under SMPS side were analyzed based Inc, (2009), 6-42. on the HF parasitic parameters, which can improve 3. Attaianese C., Nardi V., Tomasso G., EMC of power the CE measurement uncertainty. converters: The self-compatibility approach, IET 2) The CM and DM models for the two line SMPS were Electric Power Applications, 1(6) (2007), 862-869. established due to the balanced and unbalanced 4. Wei Yan, Qiang Tang, Enrong Wang, Radiated current. emission mechanism for semi-active control 3) Three CE noise mitigation methods were proposed strategy of magneto-rheological damper, in the paper, such as the capacitor shunt between International Journal of Applied Electromagnetics

Researches in Engineering the source and drain electrodes of MOSFET, CM and Mechanics, 51(2) (2016), 185-198. choke and crosstalk choke, and the capacitors 5. Wei Yan, Jing Yu, Qiang Tang, Analysis and mitigation on conducted electromagnetic

nal of nal matrix, which can improve the safety and EMI performance of SMPS. interference of semi-active control strategy for our magneto-rheological damper, International Journal The experiment results show that the CE noises of Applied Electromagnetics and Mechanics, 50(2)

obal J of the power concentrator and colonoscopy can be (2016), 247-254. Gl reduced very well by employing the present 6. European Committee for Electrotechnical approaches. Standardization, EN 55022-2010: Information technology equipment- Radio disturbance VIII. ACKNOWLEDGMENT characteristics- Limits and methods of This paper is supported by Project Supported measurement, Brussels, Belgium: The European by National Natural Science Foundation of China Commission and the European Free Trade (51475246); National Natural Science Foundation of Association, (2010). Jiangsu Province(BK20161019); University Science 7. Chang Y.H., Complex programmable logic device- Research Project of Jiangsu Province (15KJB470011). based closed-loop implementation of switched-

capacitor step-down DC-DC converter for multiple output choices, IET Electric Power Applications, 1(6) (2007), 926-936. 8. Xiaopeng Dong, Haixiao Weng, Beetner D.G., Hubing T.H., Approximation of Worst Case Crosstalk at High Frequencies, Electromagnetic Compatibility, IEEE Transactions on, 53(1) (2011), 202-208. 9. Yan Wei, Zhao Yang, Wang Enrong, et a, Investigation and Reduction on Conducted Electromagnetic Interference Noise Mechanism for Complex Power Electronics Systems, Proceedings of the CSEE, 32(30) (2012), 156-162.

10. L.H. Kim，J.S. Yu，W.C. Lee, et al, Conducted EMI

reduction of PWM inverter for AC motor drive 201 systems, International Journal of Applied

Electromagnetics and Mechanics, 24(3) (2006), 195- Year

207. 35 11. X. Wang，Z. Liu，Z. Zhou, Rapid computation model for accurate evaluation of electromagnetic interference shielding effectiveness of fabric with hole based on equivalent coefficient, International Journal of Applied Electromagnetics and Mechanics, 47(1) (2015), 177-185. 12. See Kye Yak, Network for conducted EMI diagnosis,

I ue II Version Electronic Letter, 35(17) (1999), 1446-1447. s 13. Mardiguian M., An alternative method for characterizing EMI filter, IEEE International Symposium on Electromagnetic Compatibility, 2 (1999), 882-886. 14. Ting Guo, Chen D.Y., Separation of the common- mode and differential-mode conducted EMI noise, Volume XVII Is

IEEE Transaction on Power electronics, 11(3) (1996), 480-488. () 15. Bhargava A., Pommerenke D., Kam K.W. et al, DC- DC Buck Converter EMI Reduction Using PCB Layout Modification, Electromagnetic Compatibility, IEEE Transactions on, 53(3) (2011), 806-813. 16. Mukherjee R., Patra A., Banerjee S., Impact of a Frequency Modulated Pulsewidth Modulation (PWM) Switching Converter on the Input Power System Quality, Power Electronics, IEEE

Transactions on, 25(6) (2010), 1450-1459. Researches in Engineering 17. Tripathi J.N., Mukherjee J., Apte P.R., et al, Selection and placement of decoupling capacitors in high speed systems, Electromagnetic Compatibility ournal of ournal Magazine, IEEE, 2(4) (2013), 72-78. 18. Wu W., Sun Y., Lin Z. et al, A Modified LLCL Filter obal J

With the Reduced Conducted EMI Noise, Power Gl Electronics, IEEE Transactions on, 29(7) (2014), 3393-3402. 19. Lei Xing, Jian Sun, Conducted Common-Mode EMI Reduction by Impedance Balancing, Power Electronics, IEEE Transactions on, 27(3) (2012), 1084-1089.

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( Researches in Engineering ournal of ournal obal J l G

Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram y Daniel L. Stevens & Stephanie A. Schuckers Air Force Research Laborator Abstract- Digital intercept receivers are currently moving away from Fourier-based analysis and towards classical time-frequency analysis techniques for the purpose of analyzing low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept frequency modulated continuous wave radar signals through utilization and direct comparison of the Spectrogram versus the Scalogram. Two different triangular modulated frequency modulated continuous wave signals were analyzed. The following metrics were used for evaluation: percent error of: carrier frequency, modulation bandwidth, modulation period, chirp rate, and time-frequency localization (x and y direction). Also used were: percent detection, lowest signal-to-noise ratio for signal detection, and plot (processing) time. Experimental results demonstrate that overall, the Spectrogram produced more accurate characterization metrics than the Scalogram. An improvement in performance may well translate into saved equipment and lives.

GJRE-F Classification: FOR Code: 090609

LowProbabilityofInterceptTriangularModulatedFrequencyModulatedContinuousWaveSignalCharacterizationComparisonusingtheSpectrogramandtheScalogram

Strictly as per the compliance and regulations of :

© 2017. Daniel L. Stevens & Stephanie A. Schuckers. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram1

Daniel L. Stevens α & Stephanie A. Schuckers σ

Abstract- Digital intercept receivers are currently moving away measure the target’s range and Doppler [MIL02], 201 from Fourier-based analysis and towards classical time- [LIW08]. Triangular modulated FMCW is the waveform frequency analysis techniques for the purpose of analyzing low that is employed in this paper. Year probability of intercept radar signals. This paper presents the

Time-frequency signal analysis involves the novel approach of characterizing low probability of intercept 37 analysis and processing of signals with time-varying frequency modulated continuous wave radar signals through utilization and direct comparison of the Spectrogram versus frequency content. Such signals are best represented the Scalogram. Two different triangular modulated frequency by a time-frequency distribution [PAP95], [HAN00], modulated continuous wave signals were analyzed. The which is intended to show how the energy of the signal I ersion following metrics were used for evaluation: percent error of: is distributed over the two-dimensional time-frequency carrier frequency, modulation bandwidth, modulation period, plane [WEI03], [LIX08], [OZD03]. Processing of the chirp rate, and time-frequency localization (x and y direction). signal may then exploit the features produced by the ue II V Also used were: percent detection, lowest signal-to-noise ratio concentration of signal energy in two dimensions (time for signal detection, and plot (processing) time. Experimental and frequency), instead of only one dimension (time or results demonstrate that overall, the Spectrogram produced frequency) [BOA03], [LIY03]. Since noise tends to more accurate characterization metrics than the Scalogram. An improvement in performance may well translate into saved spread out evenly over the time-frequency domain, while equipment and lives. signals concentrate their energies within limited time intervals and frequency bands; the local SNR of a noisy I. Introduction signal can be improved simply by using time-frequency Volume XVII Iss

analysis [XIA99]. Also, the intercept receiver can requency Modulated Continuous Wave (FMCW) () increase its processing gain by implementing time- signals are frequently encountered in modern frequency signal analysis [GUL08]. radar systems [WAN10], [WON09], [WAJ08]. The F Time-frequency distributions are useful for the frequency modulation spreads the transmitted energy visual interpretation of signal dynamics [RAN01]. An over a large modulation bandwidth ΔF, providing good experienced operator can quickly detect a signal and range resolution that is critical for discriminating targets extract the signal parameters by analyzing the time- from clutter. The power spectrum of the FMCW signal is frequency distribution [ANJ09]. nearly rectangular over the modulation bandwidth, so The Spectrogram is defined as the magnitude non-cooperative interception is difficult. Since the squared of the Short-Time Fourier Transform (STFT)

transmit waveform is deterministic, the form of the return Researches in Engineering [HIP00], [HLA92], [MIT01], [PAC09], [BOA03]. For non- signals can be predicted. This gives it the added stationary signals, the STFT is usually in the form of the advantage of being resistant to interference (such as Spectrogram [GRI08]. of nal jamming), since any signal not matching this form can

The STFT of a signal x(u) is given in equation 1 as: our be suppressed [WIL06]. Consequently, it is difficult for an intercept receiver to detect the FMCW waveform and ( , ; ) = ( ) ( ) (1) measure the parameters accurately enough to match +∞ −푗2휋푓푢 the jammer waveform to the radar waveform [PAC09]. 퐹푥 Where푡 푓 ℎ h(t)∫− ∞is 푥a푢 shortℎ 푢 −time푡 푒 analysis푑푢 window J Global The most popular linear modulation utilized localized around t=0 and f=0. Because multiplication is the triangular FMCW emitter [LIA09], since it can by the relatively short window h(u-t) effectively

suppresses the signal outside a neighborhood around Author α: Air Force Research Laboratory Rome, NY 13441. e-mail: [email protected] the analysis point u=t, the STFT is a ‘local’ spectrum of Auhtor σ: Department of Electrical and Computer Engineering, Clarkson the signal x(u) around t. Think of the window h(t) as University Potsdam, NY 13699. e-mail: [email protected] sliding along the signal x(u) and for each shift h(u-t) we

1 compute the usual Fourier transform of the product Approved for Public Release; Distribution Unlimited: CaseNumber: 88ABW-2017 -1873, 25-Apr-2017 function x(u)h(u-t). The observation window allows

localization of the spectrum in time, but also smears the function (the mother wavelet) by translations and spectrum in frequency in accordance with the dilations: uncertainty principle, leading to a trade-off between time resolution and frequency resolution. In general, if the ( , ; ) = ( ) , ( ) (3) window is short, the time resolution is good, but the +∞ ∗ 푥 −∞/ 푡 푎 frequency resolution is poor, and if the window is long, where 푇 , 푡(푎) Ψ= | | ∫ 푥 푠 Ψ. 푠 푑푠The va riable a −1 2 푠−푡 the frequency resolution is good, but the time resolution corresponds푡 푎 to a scale factor, in the sense that taking Ψ 푠 푎 Ψ � 푎 � is poor. |a|>1 dilates the wavelet Ψ and taking |a|<1 The STFT was the first tool devised for analyzing compresses Ψ. By definition, the wavelet transform is a signal in both time and frequency simultaneously. For more a time-scale than a time-frequency representation. analysis of human speech, the main method was, and However, for wavelets which are well localized around a still is, the STFT. In general, the STFT is still the most non-zero frequency ν_0 at a scale =1 , a time-frequency widely used method for studying non-stationary signals interpretation is possible thanks to the formal

201 [COH95]. identification = . The Spectrogram (the squared modulus of the The wavelet휈0 transform is of interest for the

Year 푎 STFT) is given by equation 2 as: analysis of non휈 -stationary signals, because it provides

still another alternative to the STFT and to many of the 38 ( , ) = ( ) ( ) (2)

2 quadratic time-frequency distributions. The basic +∞ −푗2휋푓푢 푆푥 T푡h푓e Spectrog�∫−∞ 푥 푢ramℎ 푢is− a푡 푒real-valued푑푢� and non- difference between the STFT and the wavelet transform negative distribution. Since the window h of the STFT is is that the STFT uses a fixed signal analysis window, assumed of unit energy, the Spectrogram satisfies the whereas the wavelet transform uses short windows at global energy distribution property. Thus we can high frequencies and long windows at low frequencies. interpret the Spectrogram as a measure of the energy of This helps to diffuse the effect of the uncertainty principle by providing good time resolution at high

ue II Version I ue II Version the signal contained in the time-frequency domain s centered on the point (t, f) and whose shape is frequencies and good frequency resolution at low frequencies. This approach makes sense especially independent of this localization. Here are some properties of the Spectrogram: when the signal at hand has high frequency components for short durations and low frequency 1) Time and Frequency covariance- The Spectrogram components for long durations. The signals preserves time and frequency shifts, thus the encountered in practical applications are often of this Volume XVII Is spectrogram is an element of the class of quadratic type.

time-frequency distributions that are covariant by The wavelet transform allows localization in both () translation in time and in frequency (i.e. Cohen’s the time domain via translations of the mother wavelet, class); and in the scale (frequency) domain via dilations. The 2) Time-Frequency Resolution- The time-frequency wavelet is irregular in shape and compactly supported, resolution of the Spectrogram is limited exactly as it thus making it an ideal tool for analyzing signals of a is for the STFT; there is a trade-off between time transient nature; the irregularity of the wavelet basis resolution and frequency resolution; lends itself to analysis of signals with discontinuities or 3) Interference Structure- As it is a quadratic (or sharp changes, while the compactly supported nature of bilinear) representation, the Spectrogram of the sum wavelets enables temporal localization of a signal’s of two signals is not the sum of the two features [BOA03]. Unlike many of the quadratic Researches in Engineering Spectrograms (quadratic superposition principle); functions such as the Wigner-Ville Distribution (WVD)

of there is a cross-Spectrogram part and a real part. and Choi-Williams Distribution (CWD), the wavelet

nal Thus, as for every quadratic distribution, the transform is a linear transformation, therefore cross-term Spectrogram presents interference terms; however, interference is not generated. There is another major those interference terms are restricted to those difference between the STFT and the wavelet transform; the STFT uses sines and cosines as an orthogonal basis

obal Jour regions of the time-frequency plane where the

Gl signals overlap. Thus if the signal components are set to which the signal of interest is effectively correlated sufficiently distant so that their Spectrograms do not against, whereas the wavelet transform uses special overlap significantly, then the interference term will ‘wavelets’ which usually comprise an orthogonal basis nearly be identically zero [ISI96], [COH95], [HLA92]. set. The wavelet transform then computes coefficients, The Scalogram is defined as the magnitude which represents a measure of the similarities, or squared of the wavelet transform, and can be used as a correlation, of the signal with respect to the set of time-frequency distribution [COH02], [GAL05], [BOA03]. wavelets. In other words, the wavelet transform of a The idea of the wavelet transform (equation (3)) signal corresponds to its decomposition with respect to is to project a signal x on a family of zero-mean a family of functions obtained by dilations (or functions (the wavelets) deduced from an elementary

©2017 Global Journals Inc. (US) Low Probability of Intercept Triangular Modulated Frequency Modulated Continuous Wave Signal Characterization Comparison using the Spectrogram and the Scalogram contractions) and translations (moving window) of an II. Methodology analyzing wavelet. A filter bank concept is often used to describe The methodologies detailed in this section the wavelet transform. The wavelet transform can be describe the processes involved in obtaining and interpreted as the result of filtering the signal with a set comparing metrics between the classical time-frequency of bandpass filters, each with a different center analysis techniques of the Spectrogram and the frequency [GRI08], [FAR96], [SAR98], [SAT98]. Scalogram for the detection and characterization of low Like the design of conventional digital filters, the probability of intercept triangular modulated FMCW design of a wavelet filter can be accomplished by using radar signals. a number of methods including weighted least squares The tools used for this testing were: MATLAB [ALN00], [GOH00], orthogonal matrix methods [ZAH99], (version 7.12), Signal Processing Toolbox (version 6.15), nonlinear optimization, optimization of a single Wavelet Toolbox (version 4.7), Image Processing parameter (e.g. the passband edge) [ZHA00], and a Toolbox (version 7.2), Time-Frequency Toolbox (version 1.0) (http://tftb.nongnu.org/). method that minimizes an objective function that 201 bounds the out-of-tile energy [FAR99]. All testing was accomplished on a desktop

Here are some properties of the wavelet computer (HP Compaq, 2.5GHz processor, AMD Athlon Year transform: 1) The wavelet transform is covariant by 64X2 Dual Core Processor 4800+, 2.00GB Memory translation in time and scaling. The corresponding (RAM), 32 Bit Operating System). 39 group of transforms is called the Affine group; 2) The Testing was performed for 2 different triangular signal x can be recovered from its wavelet transform via modulated FMCW waveforms. For each waveform, the synthesis wavelet; 3) Time and frequency parameters were chosen for academic validation of resolutions, like in the STFT case, are related via the signal processing techniques. Due to computer Heisenberg-Gabor inequality. However in the wavelet processing resources they were not meant to represent transform case, these two resolutions depend on the real-world values. The number of samples for each test frequency: the frequency resolution becomes poorer was chosen to be either 256 or 512, which seemed to I II Version sue and the time resolution becomes better as the analysis be the optimum size for the desktop computer. Testing frequency grows; 4) Because the wavelet transform is a was performed at three different SNR levels: 10dB, 0dB, linear transform, it does not contain cross-term and the lowest SNR at which the signal could be interferences [GRI07], [LAR92]. detected. The noise added was white Gaussian noise, A similar distribution to the Spectrogram can be which best reflects the thermal noise present in the IF olume XVII Is defined in the wavelet case. Since the wavelet transform section of an intercept receiver [PAC09]. Kaiser V ) behaves like an orthonormal basis decomposition, it can windowing was used, when windowing was applicable. ( be shown that it preserves energy: 50 runs were performed for each test, for statistical | ( , ; )| = (4) purposes. The plots included in this paper were done at +∞ 2 푑푎 a threshold of 5% of the maximum intensity and were 2 where is∬ the−∞ energy푇푥 푡 푎 ofΨ . 푑푡This푎 leads 퐸푥 us to define the linear scale (not dB) of analytic (complex) signals; the Scalogram (equation (4)) of as the squared modulus color bar represented intensity. The signal processing 푥 of the wavelet퐸 transform. 푥It is an energy distribution of tools used for each task were the Spectrogram and the the signal in the time-scale 푥plane, associated with the Scalogram. measure . Task 1 consisted of analyzing a triangular 푑푎 modulated FMCW signal (most prevalent LPI radar As is2 the case for the wavelet transform, the Researches in Engineering 푎 time and frequency resolutions of the Scalogram are waveform [LIA09]) whose parameters were: sampling related via the Heisenberg-Gabor principle. frequency=4KHz; carrier frequency=1KHz; modulation The interference terms of the Scalogram, as for bandwidth=500Hz; modulation period=.02sec. the spectrogram, are also restricted to those regions of Task 2 was similar to Task 1, but with different the time-frequency plane where the corresponding parameters: sampling frequency=6KHz; carrier obal Journal of obal Journal signals overlap. Therefore, if two signal components are frequency=1.5KHz; modulation bandwidth=2400Hz; l G sufficiently far apart in the time-frequency plane, their modulation period=.15sec. The different parameters cross-Scalogram will be essentially zero [ISI96], were chosen to see how the different shapes/heights of [HLA92]. the triangles of the triangular modulated FMCW would For this paper, the Morlet Scalogram will be affect the metrics. used. The Morlet wavelet is obtained by taking a After each particular run of each test, metrics complex sine wave and by localizing it with a Gaussian were extracted from the time-frequency representation. envelope. The Mexican hat wavelet isolates a single The different metrics extracted were as follows: bump of the Morlet wavelet. The Morlet wavelet has 1) Plot (processing) time: Time required for plot to be good focusing in both time and frequency [CHE09]. displayed.

2) Percent detection: Percent of time signal was Threshold percentages were determined based detected - signal was declared a detection if any on visual detections of low SNR signals (lowest SNR at portion of each of the signal components (4 chirp which the signal could be visually detected in the time- components for triangular modulated FMCW) frequency representation) (see Figure 1). exceeded a set threshold (a certain percentage of the maximum intensity of the time-frequency representation).

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Figure 1: Threshold percentage determination. This plot is an amplitude vs. time (x-z view) of the Spectrogram of a triangular modulated FMCW signal (256 samples, with SNR= -3dB). For visually detected low SNR plots (like this one), the percent of max intensity for the peak z-value of each of the signal components (the 2 legs for each of the 2 triangles of the triangular modulated FMCW) was noted (here 98%, 60%, 95%, 63%), and the lowest of these 4 values was recorded (60%). Ten test runs were performed for both time-frequency analysis tools (Spectrogram and Scalogram) for this waveform. The average of these recorded low values was determined and then assigned as the

XVII Issue II Version I II Version XVII Issue threshold for that particular time-frequency analysis tool. Note - the threshold for the Spectrogram is 60%. Thresholds were assigned as follows: automatically during the plotting process. From the olume

V Spectrogram (60%); Scalogram (50%). threshold plot, the signal was declared a detection if any )

For percent detection determination, these portion of each of the signal components was visible ( threshold values were included in the time-frequency (see Figure 2). plot algorithms so that the thresholds could be applied

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obal J Figure 2: Percent detection (time-frequency). This plot is an frequency vs. time (x-y view) of the Spectrogram of a l

G triangular modulated FMCW signal (256 samples, with SNR= 10dB) with threshold value automatically set to 60%. From this threshold plot, the signal was declared a (visual) detection because at least a portion of each of the 4 signal components (the 2 legs for each of the 2 triangles of the triangular modulated FMCW) was visible. 3) Carrier frequency: The frequency corresponding to the maximum intensity of the time-frequency representation (see Figure 3).

Figure 3: Determination of carrier frequency. Spectrogram of a triangular modulated FMCW signal (256 samples, 201 SNR=10dB). From the frequency-intensity (y-z) view, the maximum intensity value is manually determined. The

Year frequency corresponding to the max intensity value is the carrier frequency (here fc=984.4 Hz).

41 4) Modulation bandwidth: Distance from highest max intensity values for these test runs was 20%. This frequency value of signal (at a threshold of 20% was adopted as the threshold value, and is maximum intensity) to lowest frequency value of representative of what is obtained when performing

signal (at same threshold) in Y-direction (frequency). manual measurements. This 20% threshold was also The threshold percentage was determined adapted for determining the modulation period and the based on manual measurement of the modulation time-frequency localization (both are described below). bandwidth of the signal in the time-frequency For modulation bandwidth determination, the representation. This was accomplished for ten test runs 20% threshold value was included in the time-frequency I II Version sue of each time-frequency analysis tool (Spectrogram and plot algorithms so that the threshold could be applied

Scalogram), for each of the 2 waveforms. During each automatically during the plotting process. From the manual measurement, the max intensity of the high and threshold plot, the modulation bandwidth was manually low measuring points was recorded. The average of the measured (see Figure 4).

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Figure 4: Modulation bandwidth determination. Spectrogram of a triangular modulated FMCW signal (256 samples,

SNR=10dB) with threshold value automatically set to 20%. From this threshold plot, the modulation bandwidth was of obal Journal l measured manually from the highest frequency value of the signal (top white arrow) to the lowest frequency value of G the signal (bottom white arrow) in the y-direction (frequency)

5) Modulation period: Distance from highest automatically during the plotting process. From the frequency value of signal (at a threshold of 20% threshold plot, the modulation period was manually

maximum intensity) to lowest frequency value of measured (see Figure 5).

signal (at same threshold) in X-direction (time).

For modulation period determination, the 20% threshold value was included in the time-frequency plot algorithms so that the threshold could be applied

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42 SNR=10dB) with threshold value automatically set to 20%. From this threshold plot, the modulation period was measured manually from the highest frequency value of the signal (top white arrow) to the lowest frequency value of the signal (bottom white arrow) in the x-direction (time)

6) Time-frequency localization: Measure of the frequency plot algorithms so that the threshold could be thickness of a signal component (at a threshold of applied automatically during the plotting process. From 20% maximum intensity on each side of the the threshold plot, the time-frequency localization was component) – converted to % of entire X-Axis, and manually measured (see Figure 6). % of entire Y-Axis. For time-frequency localization determination,

the 20% threshold value was included in the time-

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Researches in Engineering Figure 6: Time-frequency localization determination. Spectrogram of a triangular modulated FMCW signal (256 samples, SNR=10dB) with threshold value automatically set to 20%. From this threshold plot, the time-frequency

ournal of ournal localization was measured manually from the left side of the signal (left white arrow) to the right side of the signal (right white arrow) in both the x-direction (time) and the y-direction (frequency). Measurements were made at the

obal J center of each of the 4 ‘legs’, and the average values were determined. Average time and frequency ‘thickness’ l

G values were then converted to: % of entire x-axis and % of entire y-axis. 7) Chirp rate: (modulation bandwidth)/(modulation plot algorithms so that the thresholds could be applied

period) automatically during the plotting process. From the

8) Lowest detectable SNR: The lowest SNR level at threshold plot, the signal was declared a detection if any

which at least a portion of each of the signal portion of each of the signal components was visible. components exceeded the set threshold listed in the The lowest SNR level for which the signal was declared percent detection section above. a detection is the lowest detectable SNR (see Figure 7).

For lowest detectable SNR determination, these threshold values were included in the time-frequency

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Figure 7: Lowest detectable SNR. This plot is an frequency vs. time (x-y view) of the Spectrogram of a triangular 43 modulated FMCW signal (256 samples, with SNR= -3dB) with threshold value automatically set to 60%. From this threshold plot, the signal was declared a (visual) detection because at least a portion of each of the 4 signal components (the 2 legs for each of the 2 triangles of the triangular modulated FMCW) was visible. Note that the signal portion for the 60% max intensity (just above the ‘x’ in ‘max’) is barely visible, because the threshold for the Spectrogram is 60%. For this case, any lower SNR would have been a non-detect. Compare to Figure 2, which is the same plot, except that it has an SNR level equal to 10dB.

The data from all 50 runs for each test was used III. Results I II Version sue to produce the actual, error, and percent error for each Table 1 presents the overall test metrics for the of these metrics listed above. two classical time-frequency analysis techniques used

The metrics from the Spectrogram were then in this testing (Spectrogram versus Scalogram). compared to the metrics from the Scalogram. By and large, the Spectrogram outperformed the Scalogram, as olume XVII Is

will be shown in the results section. V

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Table 1: Overall test metrics (average percent error: carrier frequency, modulation bandwidth, modulation period, chirp rate; average: percent detection, lowest detectable snr, plot time, time-frequency localization (as a percent of x ( axis and y axis) for the two classical time-frequency analysis techniques (Spectrogram versus Scalogram).

parameters Spectrogram Scalogram

carrier frequency 6.83% 8.26%

modulation bandwidth 16.60% 28.17%

modulation period 0.68% 0.72% Researches in Engineering

chirp rate 16.25% 28.47%

percent detection 70.0% 62.22%

lowest detectable snr -3.67db -2.67db of obal Journal l G plot time 3.28s 4.16s

time-frequency localization-x 2.88% 4.51%

time-frequency localization-y 5.75% 9.0%

From Table 1, the Spectrogram outperformed Figure 8 shows comparative plots of the the Scalogram in every metrics category. Spectrogram (left) vs. the Scalogram (right) (triangular

modulated FMCW signal – Task 1) at SNRs of 10dB (top), 0dB (middle), and -3dB (bottom).

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obal J l Figure 8: Comparative plots of the triangular modulated FMCW (task 1) low probability of intercept radar signals G (Spectrogram (left-hand side) vs. the Scalogram (right-hand side)). The SNR for the top row is 10dB, for the middle row is 0dB, and for the bottom row is -3dB. In general, the Spectrogram signals appear more localized (‘thinner’) than do the Scalogram signals. In addition, the Spectrogram signals appear more readable than the Scalogram signals at every SNR level. Figure 9 shows comparative plots of the Spectrogram (left) vs. the Scalogram (right) (triangular modulated FMCW signal – Task 2) at SNRs of 10dB (top), 0dB (middle), and -3dB (bottom).

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Figure 9: Comparative plots of the triangular modulated FMCW (task 2) low probability of intercept radar signals (Spectrogram (left-hand side) vs. the Scalogram (right-hand side)). The SNR for the top row is 10dB, for the middle row is 0dB, and for the bottom row is -3dB. In general, the Spectrogram signals appear more localized (‘thinner’) than do the Scalogram signals. In addition, the Spectrogram signals appear more readable than the Scalogram obal Journal of obal Journal signals at every SNR level. l G IV. Discussion the Time-Frequency representation. Figure 8 and Figure 9 show clearly that the signals in the Spectrogram plots This section will elaborate on the results from are more readable than those in the Scalogram plots, the previous section. which account for the Spectrogram’s better average From Table 1, the Spectrogram outperformed the Scalogram in every category. The Spectrogram’s percent detection and lowest detectable SNR. At reduction of cross-term interference is grounds for its relatively low frequencies (as in this paper), wavelets better plot time. Average percent detection and lowest (Scalograms), because of their multi-resolution analysis detectable SNR are both based on visual detection in basis, are better resolved (localized) in frequency and

more poorly resolved (localized) in time. Therefore for 3. [BOA03] Boashash, B., Time Frequency Signal relatively low frequencies, the best waveforms to be Analysis and Processing: A Comprehensive analyzed by wavelets (Scalograms) are tonals. In Reference. Elsevier, Oxford, England, 2003. addition, the irregularity of the wavelet (Scalogram) 4. [CHE09] Chen, C., He, M., Jin, H., Li, H., Shen, basis lends itself to analysis of signals with Z., A Novel Method for Extraction of In-Pulse discontinuities (such as frequency hopping signals Feature of Multi-Component LFM Signal. ICEMI (tonals)). Also, since the wavelet is irregular in shape 2009, pp. 4-627 – 4-630, 2009. and compactly supported, it makes it an ideal tool for 5. [COH02] Cohen, L., The Wavelet Transform and analyzing signals of transient nature (such as the Time-Frequency Analysis. in: Debnath, L., Wavelet frequency hopping signals (tonals)). Therefore as the Transforms and Signal Processing, Birkhauser, pp. signal goes from being ‘flat’ (i.e. a tonal) signal, to more 3-22, 2002. ‘upright’ (i.e. a triangular modulated FMCW) signal, the 6. [COH95] Cohen, L., Time-Frequency Analysis. Scalogram of this signal becomes more poorly resolved Prentice Hall, Upper Saddle River, NJ, 1995.

201 (localized), i.e. ‘fatter’, accounting for the Scalogram’s 7. [FAR96] Farrell, T.C., Prescott, G., A Low poorer metrics in the categories of modulation Probability of Intercept Signal Detection Receiver

Year bandwidth, modulation period, chirp rate, carrier Using Quadrature Mirror Filter Bank Trees. IEEE

frequency, time-frequency localization (x), and time- Proceedings, pp. 1558-1561, 1996. 46 frequency localization (y). 8. [FAR99] Farrell, T., Prescott, G., A Method for Finding Orthogonal Wavelet Filters with Good V. Conclusions Energy Tiling Characteristics. IEEE Transactions on Digital intercept receivers, whose main job is to Signal Processing, Vol. 47, No. 1, pp. 220-223, Jan. detect and extract parameters from low probability of 1999. intercept radar signals, are currently moving away from 9. [GAL05] Galleani, L., Cohen, L., Noga, A., A Fourier-based analysis and towards classical time- Time-Frequency Approach to the Adjustable frequency analysis techniques, such as the Bandwidth Concept. Digital Signal Processing, Vol. Spectrogram, and Scalogram, for the purpose of 16, Issue 5, pp. 454-467, Sept. 2006. analyzing low probability of intercept radar signals. 10. [GOH00] Goh, C., Lim, T., A WLS Algorithm for the Design of Low-Delay Quadrature Mirror Filter XVII Issue II Version I II Version XVII Issue Based on the research performed for this paper (the novel direct comparison of the Spectrogram versus the Banks. Proceedings of the IEEE International Symposium on Circuits and Systems, Vol. 1, pp.

olume Scalogram for the signal analysis of low probability of V intercept triangular modulated FMCW radar signals) it 615-618, May 2000. )

was shown that the Spectrogram by-and-large 11. [GRI07] Grishin, Y., Janczak, D., Computer- ( outperformed the Scalogram for analyzing these low Aided Methods of the LPI Radar Signal Detection probability of intercept radar signals - for reasons and Classification. Proc. of SPIE Vol. 6937, pp. 1-5, brought out in the discussion section above. More 2007. accurate characterization metrics could well translate 12. [GRI08] Grishin, Y., Interferences Excision Via into saved equipment and lives. Time-Frequency Distribution in Radio Future plans include continuing to analyze low Communication Systems. EMD 2008, XVIII-th probability of intercept radar waveforms (such as the International Conference on Electromagnetic frequency hopping and the triangular modulated Disturbances, Vilnius, Lithuania, pp. 85-88, 25-26 September 2008. FMCW), using additional time-frequency analysis Researches in Engineering 13. [GUL08] Gulum, T., Pace, P., Cristi, R., techniques. Extraction of Polyphase Radar Modulation References Références Referencias Parameters Using a Wigner-Ville Distribution-Radon Transform. IEEE International Conference on ournal of ournal 1. [ALN00] Al-Namiy, F., Nigam, M., On the Design Acoustics, Speech, and Signal Processing, Las of 2-Band FIR QMF Filter Banks Using WLS Vegas, NV, April 2008. obal J l Techniques. Proceedings of the Fourth IEEE 14. [HAN00] Han, S., Hong, H., Seo, D., Choi, J., G International Conference on High Performance Target Position Extraction Based on Instantaneous Computing in the Asia-Pacific Region, Vol. 2, pp. Frequency Estimation in a Fixed-Reticle Seeker.

772-776, May 2000. Opt. Eng., Vol. 39, pp. 2568-2573, September 2000.

2. [ANJ09] Anjaneyulu, L., Murthy, N., Sarma, N., A 15. [HIP00] Hippenstiel, R., Fargues, M., Novel Method for Recognition of Modulation Code Moraitakis, I., Williams, C., Detection and Parameter of LPI Radar Signals. International Journal of Recent Estimation of Chirped Radar Signals. Final Report, Trends in Engineering, Vol. 1, No. 3, pp. 176-180, Naval Postgraduate School, Monterey, CA, Jan. 10,

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16. [HLA92] Hlawatsch, F., Boudreaux-Bartels, G.F., 29. [SAR98] Sarkar, T., Su, C., et al., A Tutorial on Linear and Quadratic Time-Frequency Signal Wavelets from an Electrical Engineering Representations. IEEE Signal Processing Mag., Vol. Perspective, Part 1: Discrete Wavelet Techniques. 9, No. 2, pp. 21-67, April 1992. IEEE Antennas and Propagation Magazine, Vol. 40, 17. [ISI96] Auger, F., Flandrin, P., Goncalves, P., No. 5, pp. 49-70, October 1998. Lemoine, O., Time-Frequency Toolbox Users 30. [SAT98] Sarkar, T., Su, C., A Tutorial on Manual. Centre National de la Recherche Wavelets from an Electrical Engineering Scientifique and Rice University, 1996. Perspective, Part 2: The Continuous Case. IEEE 18. [LAR92] Lari, F., Zakhor, A., Automatic Antennas and Propagation Magazine, Vol. 40, No. Classification of Active Sonar Data Using Time- 6, pp. 36-49, December 1998. Frequency Transforms. Proceedings of IEEE-SP 31. [WAJ08] Wang, Y., Jiang, Y., Detection and International Symposium on Time-Frequency and Parameter Estimation of Multicomponent LFM Time-Scale Analysis, Victoria, BC, pp. 21-24, Oct. 4- Signal Based on the Cubic Phase Function.

6, 1992. EURASIP Journal on Advances in Signal 201 19. [LIA09] Liang, Y., Zhang, L., Xing, M., Bao, Z., Processing, Vol. 2008, Article ID 743985, pp. 1-7,

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Multi-LFM Signals. Journal of Electronics (China), Signals. Defence R&D Canada – Ottawa Contract Vol. 20, No. 3, pp. 161-166, May 2003. Report 2009-142, September 2009. ( 23. [MIL02] Milne, P., Pace, P., Wigner Distribution 36. [XIA99] Xia, X., Chen, V., A Quantitative SNR Detection and Analysis of FMCW and P-4 Analysis for the Pseudo Wigner-Ville Distribution. Polyphase LPI Waveforms. Proceedings of ICASSP, IEEE Transactions on Signal Processing, Vol. 47, Orlando, FL, pp. 3944-3947, 2002. No. 10, pp. 2891-2894, October, 1999. 24. [MIT01] Mitra, S., Digital Signal Processing, A 37. [ZAH99] Zahhad, A., Sabah, M., Design of Computer-Based Approach, Second Edition. Selective M-Channel Perfect Reconstruction FIR McGraw-Hill, Boston, MA, 2001. Filter Banks. IEE Electronics Letters, Vol. 35, No. 15, 25. [OZD03] Ozdemir, A., Time-Frequency pp. 1223-1225, 1999.

Component Analyzer. Dissertation, Bilkent 38. [ZHA00] Zhang, Z., Jiao, L., A Simple Method for Researches in Engineering University, Ankara, Turkey, Sept. 2003. Designing Pseudo QMF Banks. Proceedings of the 26. [PAC09] Pace, P., Detecting and Classifying Low IEEE International Conference on Communication Probability of Intercept Radar. Artech House, Technology, Vol. 2, pp. 1538-1541, Aug. 2000. Norwood, MA, 2009. 27. [PAP95] Papandreou, A., Boudreaux-Bartels, obal Journal of obal Journal G.F., Kay, S., Detection and Estimation of l G Generalized Chirps Using Time-Frequency Representations. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on Signals, Systems and Computers, pp. 50-54, 1994. 28. [RAN01] Rangayyan, R., Krishnan, S., Feature Identification in the Time-Frequency Plane by Using the Hough-Radon Transform. Pattern Recognition, Vol. 34, pp. 1147-1158, 2001.

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Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric By Faisal Al Mozahid, Dr. M Tanseer Ali & Md. Ashikur Rahman American International University-Bangladesh Abstract- The Carbon Nanotube Field Effect Transistor (CNTFET) is one of the most rising devices among the emerging technologies to extend and/or complement the traditional Silicon MOSFET as it is showing high efficiency and wide range of applications in many different fields of science and technology. Carbon Nanotube Field Effect Transistors have been explored and proposed to be the upcoming more efficient and suitable candidates for the integrated circuit (NGIC) devices of next generation. In this study, firstly, the Density of State (DOS) with different types of nanotubes considering the chirality have been reviewed. Then we have studied the carbon nanotube field effect transistor by replacing the traditional gate insulator with a material that has much higher dielectric constant. Keywords: carbon nanotube, CNT field effect transistor, CNT DOS, Gate Dielectric.

GJRE-F Classification: FOR Code: 090699

PerformanceAnalysisofEnhancedCarbonNanotubeFieldEffectTransistorCNTFETusingZirconiaasGateDielectric

Strictly as per the compliance and regulations of :

© 2017. Faisal Al Mozahid, Dr. M Tanseer Ali & Md. Ashikur Rahman. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecom mons.org/ licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric

Faisal Al Mozahid α, Dr. M Tanseer Ali σ & Md. Ashikur Rahman ρ

Abstract- The Carbon Nanotube Field Effect Transistor Hamada et al., 1992; Saito et al., 1992). Because of its

(CNTFET) is one of the most rising devices among the excellent conductivity and high dielectric properties, emerging technologies to extend and/or complement the

CNTs play a vital role in different nano electronic devices 201 traditional Silicon MOSFET as it is showing high efficiency and such as transistors, digital logic devices, memory wide range of applications in many different fields of science components, etc (Heinze et al., 2002). Year and technology. Carbon Nanotube Field Effect Transistors have been explored and proposed to be the upcoming more The fundamental strategy for improving the 49 efficient and suitable candidates for the integrated circuit performance of VLSIs is scaling down of electronic (NGIC) devices of next generation. In this study, firstly, the devices. According to the ITRS the gate length of Density of State (DOS) with different types of nanotubes MOSFETs will be less than 16 nm in 2016 (ITRS, 2003). If considering the chirality have been reviewed. Then we have this continues then the MOSFETs will reach its limiting I ersion studied the carbon nanotube field effect transistor by replacing size very soon. Thus the semiconductor industry is the traditional gate insulator with a material that has much searching for different materials to integrate with the higher dielectric constant. Carbon Nanotube Field Effect current silicon-based technology and in the long run, Transistor has been analyzed with the bandgap of 1.0882eV in ue II V possibly replace it if required. In this regard the carbon this research and ZrO2 (Zirconia) has been taken as the gate dielectric. We have also analyzed quantum capacitance, nanotube field effect transistor (CNTFET) will be the most transconductance and mobile charge behavior at different promising alternatives for its unique properties. It was drain voltage. Finally, the output characteristics of proposed demonstrated long before in 1998 (Tans et al., 1998). model has been given. Carbon nanotube field-effect transistors offer high mobility Keywords: carbon nanotube, CNT field effect transistor, for ballistic transport, high mechanical and thermal stability

CNT DOS, Gate Dielectric. with high resistance to electro migration, attracting strong Volume XVII Iss

interest as alternative high device technologies for the

() I. Introduction future nano electronics applications (Avouris et al., 2007). arbon Nanotubes are sheets of graphite rolled in Recently, a carbon nanotube transistor, which integrates the shape of a tube. Depending on chirality they ultra-short channel, thin high-k top gate insulator and

can be either metallic or semiconducting. Carbon excellent Pd source-drain contact is demonstrated using C Nanotubes were discovered by Iijima at the NEC a self-align technique (Javey et al., 2008). Fundamental Research Laboratory while he used a high This paper proposes CNTFET with ZrO2 as gate resolution transmission electron microscope (TEM) to oxide which is also one of the most promising devices. observe byproducts of carbon which had been This paper has been devised into main two sections. In generated by an arc between two carbon electrodes the first section, the mobility of CNTs has been

Researches in Engineering (Iijima, 1991). After that momentous development has discussed with analyzing the Density of State (DOS) of been achieved by understanding the characteristics and different types of nanotubes and in the second part, the proposed CNTFET device modeling has been described searching possible applications of these on of nal semiconductor technology. They have high elastic with its parameters, along with simulation results. our modulus, small weight and are predicted to be the II. Carbon Nanotube strongest fibers. Carbon Nanotube’s strength and

flexibility are their unique properties. The fascinating Carbon is an element with symbol C. Its atomic J Global electronic properties of them depend drastically on number is 6 (1s22s22p2). Carbon is a group 14 element both the diameter and the chirality of the hexagonal that resides above silicon on the periodic table. It is carbon lattice along the tube (Mintmire et al., 1992; nonmetallic and tetravalent making four electrons available to form covalent chemical bonds. Carbon has four electrons in its valance shell like silicon (1s22s22p6

Auhtor α σ ρ: Electrical and Electronic Engineering, American 3s23p2) and germanium (1s22s22p63s23p63d104s24p2).

International University-Bangladesh, Dhaka, Bangladesh. There are several allotropes of carbon like graphite, e-mail: [email protected] diamond and amorphous carbon (Carbon materials

research group, University of Kentucky). When carbon atoms are arranged in crystalline structures composed of benzene like rings, they form several allotropes that contain totally exceptional electronic properties. The physical properties of carbon vary widely with the allotropic form (List of thermal conductivities, Wikipedia). Diamond, carbon nanotubes and graphene have the highest thermal conductivity of all known materials (e.g., diamond: 900-2300 Wm1K1, carbon nanotube: 3180-3500 Wm 1K1) (Faisal and Ali, 2015) under normal conditions. Carbon Nanotubes (CNTs) are an allotrope of carbon. Carbon nanotubes have many forms, differing

201 in length, thickness and in the type of helicity and Fig. 1: Single walled carbon nanotube number of layers. It can be categorized into Single

Year Walled Carbon Nanotube (SWCNT) and Multi Walled

Carbon Nanotube (MWCNT) shown in Fig. 1 and 2. 50 The carbon nanotubes have diameters from less than 1nm to 50 nm. These possess excellent mechanical and transport properties too. The rolled graphene (CNT) can be explained by a coordinate of indices (n, m), which is known as Chiral Vector. It represents whether CNT is metallic or semiconducting and diameter of CNT. The table shown ue II Version I ue II Version s below describes “Chirality of carbon nanotube. The diameter of carbon nanotube is given by:

3a d= c-c m22+mn+n (1) π Where: Fig. 2: Multi walled carbon nanotube Volume XVII Is

ac-c = 0.142 nm is the carbon-carbon bond length

() Figure 3 and 4 shows the Density of State (DOS) of different types of nanotubes. The simulated end states are within the energy gap of

semiconducting carbon nanotubes, implying that the end states are a 1-D analogy with conventional surface states. Since the band gaps of carbon nanotubes are small, CNTs are either metallic or semi conductive. The energy band structures of carbon atom provide an occupied energy level in the band

Researches in Engineering gap depending upon the density of states and types of CNT. The (10, 0) nanotube acts as semi of conducting material since it has energy gap between nal conduction and valence band whereas the (8, 8) nanotube acts as conducting material as the valance and conduction bands are overlapping. obal Jour Gl

Fig. 3: DOS vs. Energy for (8, 8)

©20 17 Global Journals Inc. (US) Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric

Fig. 5: Planner CNTFET 201 Year

Fig. 4: DOS vs. Energy for (10, 0) ersion I ersion III. Carbon Nanotube Field Effect Transistor ue II V A Carbon Nanotube Field-Effect Transistor (CNTFET) indicates a field-effect transistor which handles a single carbon nanotube or an array of carbon nanotubes as the channel material rather silicon in the conventional MOSFET structure. CNTFET is a three-terminal (three to six layers) device consisting of a semiconducting nanotube bringing Volume XVII Iss two contacts (source and drain) and act as a carrier channel which is turned on or off electrically via the () third contact (gate). According to the fabrication geometry there are many type of CNTFET devices such as Back-gated CNTFET, Top- gated CNTFET, Wrap-around gate CNTFET, Suspended CNTFET etc. Fig. 6: I-V characteristics of proposed CNTFET (Solid (Wind et al., 2002; Chen et al., 2008; Farmer and line) Gordan, 2006; Cao et al., 2005). These are divided IV. Modelling of Cntfet broadly in two categories: Planner CNTFET and Coaxial CNTFET which are shown in Fig. 5. CNTFETs The proposed device is formed with a (10, 0) show different characteristics compared to MOSFETs CNT. So the channel diameter =0.782885nm. For gate Researches in Engineering in their theoretical experiments. In a planar gate insulation ZrO2 (k = 25) is used. Energy gap for a

structure, the p-CNTFET produces ~1500 A/m of the nanotube is given by: of nal

on-current per unit width at a gate overdrive of 0.6 V our 2aγ while p-MOSFET produces ~500 A/m at the same gate Eg = c-c (2) voltage (Cao et al., 2005). This on-current advantage channel diameter contains from the high gate capacitance and modified Where: J Global channel transport. Since an effective gate = The nearest neighbor-hopping parameter ( = 2.5- γ γ capacitance per unit width of CNTFET is about double 3.2) that of p-MOSFET, the compatibility with high gate Using γ = 3, the energy gap is 1.0882eV. The dielectrics becomes a superior advantage for parameters used in proposed model and calculations

CNTFETs (Sahoo and Mishra, 2009). are given in Table 3.

Table 1: Properties of carbon nanotube

Material Young’s modulus (GPa) Tensile strength (GPa) Electrical conductivity (mho/m) 7 Single wall nanotube ~1050 150.000 ~10 6 Multi wall nanotube ~1200 150.000 ~10 Steel 208 0.400 ~105

Wood 16 0.008 ~10-4

Table 2: CNT classifications

Type of CNTs Values of m and n State

Armchair m=n Metallic Zigzag m=0 Semiconducting 201 Semiconducting or Chiral n-m≠3×integer Semiconducting (large bandgap) Quasi-Semiconducting n- m=3×integer Semiconducting (small bandgap)

Year Table 3: Proposed parameters

52 Energy gap 1.0882 eV Gate oxide thickness 1.6 nm

CNT diameter 0.78 nm Gate dielectric (ZrO2) 25

Conductance between two leads source and Using the charge density within the device, the

drain is defined in terms of current and voltage: I = GV. NEGF transport equation is solved teratively with the Using Landauer formula (Nazarov and Blanter, 2009), posison equation until self-consistant potential

ue II Version I ue II Version conductance is expressed by the following equations: distribution is found. Finally the current is calculated s using the Landauer Böuttiker expression: 2Te2 G= (3)  h 4d∫ T ()(E fsd E) - f() E dE I=d (7) where, q is the charge of electron and h is the Planck’s h constant. T is known as the transmission function in T is the transmission probability across the source/drain; terms of energy that represents the probability of an f and f are the source/drain Fermi-Dirac distribution Volume XVII Is S D electron injected at one end of a conductor will emit at functions consistent potential; The equation is solved

() the other end. T can be expressed as: simultaneously to evaluate and characterize the ra performance of these devices.  (4) T = trace TSG 0ΓGD0 V. Simulations r a G0 G0 represents the retarded and advanced Green’s Hafnia (HfO ) adopts the same structure as function of the nanotube and ГD, ГS are the coupling of 2

the CNT to the source and the drain. The retarded zirconia (ZrO2, K=~ 25). Unlike TiO2 (k = 40), which Green’s function is calculated by: features six-coordinate Titanium in all phases, zirconia and HfO2 consists of seven- coordinate metal r -1 G0 =( EIΗ-- -∑∑SD) (5) centers (Miikkulainen et al., 2013; Faisal and Ali,

Researches in Engineering 2012). Hafnium-based oxides were introduced by Intel where, E is Fermi energy, I is the identity matrix, H is the in 2007 as a replacement for silicon oxide as a gate of Hamiltonian of the nanotube. ΣS, ΣD is the self-energy insulator in field-effect transistors (Source: INTEL). We nal terms at the source and drain coupling of the contacts simulate the I-V Characteristics of CNTFET using ZrO2 are the calculated using the broadening function of the as gate insulator for proposed model. The high-K self-energy terms at the source and drain. gate insulator and bigger CNT diameter allows higher

obal Jour The nanotube behaves as the conducting drain current. Gl channel in the CNTFET from the source to drain; it Figure 7 shows the output characteristics of the depends on the current density of the tube. The current proposed CNTFET. The channel allows the current to density is a measure of the density of flow of an flow when the gate voltage is greater than 0.3 V. So the electric current per unit area across a section. The on current is 70 μA at Vg = 2.0 V and Vd = 1.0 V and the current density is an area density described by J. The off current is 6.61e-05 μA at Vg = 0V and Vd = 1.0 V. current through an area A is simply the flux of the

current density through that area as shown below:

I =∫ J.dA (6)

©20 17 Global Journals Inc. (US) Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric

201 Year

Fig. 7: Id vs. Vd (Output characteristics) curve at Fig. 9: Quantum capacitance vs. Gate voltage different Vg ue II Version I ue II Version s Volume XVII Is

()

Fig. 10: Mobile charge behavior at gate voltage Fig. 8: Transconductance of CNTFET Quantum capacitance is associated with the Researches in Engineering In order to achieve a relatively large properties of channel material. As the density of state is transconductance the CNT must have large channel finite in a semiconductor quantum well, the Fermi level diameter. The larger the transconductance, the greater needs to move up above the conduction band edge as the gain it will deliver. As the diameter gets smaller this the charge in the quantum well increases. This of ournal reduces the carrier mobility, changing the movement of Fermi level requires energy and this transconductance. The transconductance behavior is conceptually corresponds to quantum capacitance. obal J Gl obtained at 0.78 nm diameter, with different drain Figure 9 shows the quantum capacitance versus the voltage (Fig. 8). The transconductance varies by a factor gate voltage at different drain voltages. It is clear that a of 10/V depending on the amount of voltage applied to higher quantum capacitance can be found at a gate the gate. However, the increase of VG will reduce the voltage 0.42 or 0.57 volt (for proposed model). allowed voltage signal through the drain.

Funding Information The authors have no support or funding to report. Ethics The authors’ hereby declare, this work is their own contribution and hence there would not be any ethical issues related to this manuscript.

References Références Referencias

1. Avouris, P., Z. Chen and V. Perebeinos, 2007. Carbon-based electronics. Nature Nanotechnol., 2: 605-615. DOI: 10.1038/nnano.2007.300 2. Cao, J. Q. Wang and H. Dai, 2005. Electron 201 transport in very clean, as-grown suspended carbon nanotubes. Nature Mater., 4: 745-749. DOI: Year 10.1038/nmat1478

54 3. Chen, Z., D. Farmer, S. Xu, R. Gordon and P. Fig. 11: Mobile charge behavior at drain voltage Avouris, 2008. Externally assembled gate-all-around As insulator thickness approaches the carbon nanotube field-effect transistor. IEEE nanometer range, the insulator capacitance becomes Electron Device Lett., 29: 183-183. DOI: comparable to the inversion layer capacitance, which 10.1109/LED.2007.914069 means that the QC and the centroid capacitance start 4. CMRG, 0000. Carbon Materials Research Group. to affect the gate capacitance. History of Carbon, University of Kentucky. 5. Faisal, A.M. and T. Ali, 2015. Simulations of sue II Version I II Version sue Figure 10 shows the mobile charge behavior as a function of gate voltage. It is noticed that enhanced CNTFET with HfO2 gate dielectric. Int. J. increasing the drain voltage beyond a specific value Sci. Res. Public., 5: 652-657. has no longer an effect on the shape of the curves 6. Farmer, D.B. and R.G. Gordon, 2006. Atomic layer XVII Is since the mobile charge remains constant. It is also deposition on suspended single-walled carbon observed that low drain voltage produces higher nanotubes via gas-phase noncovalent functionalization. Nano Lett., 6: 699-703. DOI:

Volume mobile charge and high drain voltage produces lower 10.1021/nl052453d

mobile charge. Also, it has been noticed that the

() mobile charge increases with the reduction in gate 7. Hamada, N., S.I. Sawada and A. Oshiyama, 1992. insulator thickness. Figure 11 shows the mobile New one-dimensional conductors: Graphitic charge behavior as a function of drain voltage. microtubules. Phys. Rev. Lett., 68: 1579-1579. DOI: 10.1103/PhysRevLett.68.1579 VI. Conclusio n 8. Heinze, S., J. Tersoff, R. Martel and V. Derycke, 2002. Carbon nanotubes as schottky barrier The proposed parameters and gate dielectric transistors. Phy. Rev. Lett., 89: 106801 -106801. of CNTFET make the transistor a challenge to develop DOI: 10.1103/PhysRevLett.89.106801 and control the aspects of it such maximum 9. Iijima, S., 1991. Helical microtubules of graphitic transconductance. We found two regions for carbon. Nature, 354: 56-58. DOI: 10.1038/354056a0 Researches in Engineering maximum transconductance. Zirconia is used in 10. ITRS, 2003. International Technology Roadma p for optical coatings and in DRAM capacitors as a high- k Semiconductors. 1st Edn., ITRS, Austin, pp: 646. dielectric and in advanced metal-oxide nal of nal 11. Javey, A., J. Guo, Q. Wang, M. Lundstrom and H.J. semiconductor devices. The advantage for proposed our Dai, 2003. Ballistic carbon nanotube field -effect CNTFET is its high dielectric constant: The dielectric transistors. Nature, 424: 654-657. DOI: constant of ZrO2 is 4-6 times higher than that of SiO2. obal J 10.1038/nature01797 In recent years, zirconium oxide (as well as doped Gl 12. Lin, K.L., 2011. Electrode dependence of filament and oxygen-deficient zirconium oxide) attracts formation in HfO resistive-switching memory. J. additional interest as a possible candidate for 2 Applied Phys., 109: 084104-084104. DOI: 10.1063/- resistive-switching memories (Lin, 2011). 1.3567915 List of thermal conductivities. VII. Acknowledgement 13. Miikkulainen, V., M. Leskelä, M. Ritala and R.L. Puurunen, 2013. Crystallinity of inorganic films grown The authors’ would like to thank Dr. M. Tanseer by atomic layer deposition: Overview and general Ali for his remarks and invaluable advises on different trends. J. Applied Phys., 113: 021301-021301. DOI: aspects of this work. 10.1063/1.4757907

©20 17 Global Journals Inc. (US) Performance Analysis of Enhanced Carbon Nanotube Field Effect Transistor (CNTFET) using Zirconia as Gate Dielectric

14. Mintmire, J.W., B.I. Dunlap and C.T. White, 1992. Are fullerene tubules metallic. Phys. Rev. Lett., 68: 631-631. DOI: 10.1103/PhysRevLett.68.631 15. Nazarov, Y.V. and Y.M. Blanter, 2009. Quantum transport: Introduction to Nanoscience. 1st Edn., Cambridge University Press, Cambridge, ISBN-10: 0521832462, pp: 581. 16. Sahoo, R. and R.R. Mishra, 2009. Simulation of carbon nanotube field effect transistors. Int. J. Electronic Eng. Res., 1: 117-125. 17. Saito, R., G. Dresselhaus and M.S. Dresselhau, 1998. Physical Properties of Carbon Nanotubes.

2nd Edn., Imperial College Press, London, ISBN-10:

1860940935, pp: 259. 201 18. Saito, R., M. Fujita, G. Dresselhaus and M.S.

Dresselhaus, 1992. Electronic structure of chiral Year

graphene tubules. Applied Phys. Lett., 60: 2204- 2204. DOI: 10.1063/1.107080 55 19. Tans, S.J., A.R.M. Verschueren and C. Dekker, 1998. Room-temperature transistor based on a single carbon nanotube. Nature, 393: 49-52. DOI: 10.1038/29954 20. Wind, S.J., J. Appenzeller, R. Martel, V. Derycke and P. Avouris, 2002. Vertical scaling of carbon nanotube field-effect transistors using top gate I II Version sue electrodes. Applied Phys. Lett., 80: 3817-3817. DOI: 10.1063/1.1480877 olume XVII Is V )

( Researches in Engineering obal Journal of obal Journal l G

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6. After Acceptance.

1. GENERAL

Before submitting your research paper, one is advised to go through the details as mentioned in following heads. It will be beneficial, while peer reviewer justify your paper for publication.

Scope

The Global Journals Inc. (US) welcome the submission of original paper, review paper, survey article relevant to the all the streams of Philosophy and knowledge. The Global Journals Inc. (US) is parental platform for Global Journal of Computer Science and Technology, Researches in Engineering, Medical Research, Science Frontier Research, Human Social Science, Management, and Business organization. The choice of specific field can be done otherwise as following in Abstracting and Indexing Page on this Website. As the all Global

Journals Inc. (US) are being abstracted and indexed (in process) by most of the reputed organizations. Topics of only narrow interest will not be accepted unless they have wider potential or consequences.

2. ETHICAL GUIDELINES

Authors should follow the ethical guidelines as mentioned below for publication of research paper and research activities.

Papers are accepted on strict understanding that the material in whole or in part has not been, nor is being, considered for publication elsewhere. If the paper once accepted by Global Journals Inc. (US) and Editorial Board, will become the copyright of the Global Journals Inc. (US).

Authorship: The authors and coauthors should have active contribution to conception design, analysis and interpretation of findings. They should critically review the contents and drafting of the paper. All should approve the final version of the paper before submission

The Global Journals Inc. (US) follows the definition of authorship set up by the Global Academy of Research and Development. According to the Global Academy of R&D authorship, criteria must be based on:

1) Substantial contributions to conception and acquisition of data, analysis and interpretation of the findings.

2) Drafting the paper and revising it critically regarding important academic content.

3) Final approval of the version of the paper to be published.

All authors should have been credited according to their appropriate contribution in research activity and preparing paper. Contributors who do not match the criteria as authors may be mentioned under Acknowledgement.

Acknowledgements: Contributors to the research other than authors credited should be mentioned under acknowledgement. The specifications of the source of funding for the research if appropriate can be included. Suppliers of resources may be mentioned along with address.

Appeal of Decision: The Editorial Board’s decision on publication of the paper is final and cannot be appealed elsewhere.

Permissions: It is the author's responsibility to have prior permission if all or parts of earlier published illustrations are used in this paper.

Please mention proper reference and appropriate acknowledgements wherever expected.

If all or parts of previously published illustrations are used, permission must be taken from the copyright holder concerned. It is the author's responsibility to take these in writing.

Approval for reproduction/modification of any information (including figures and tables) published elsewhere must be obtained by the authors/copyright holders before submission of the manuscript. Contributors (Authors) are responsible for any copyright fee involved.

3. SUBMISSION OF MANUSCRIPTS

Manuscripts should be uploaded via this online submission page. The online submission is most efficient method for submission of papers, as it enables rapid distribution of manuscripts and consequently speeds up the review procedure. It also enables authors to know the status of their own manuscripts by emailing us. Complete instructions for submitting a paper is available below.

Manuscript submission is a systematic procedure and little preparation is required beyond having all parts of your manuscript in a given format and a computer with an Internet connection and a Web browser. Full help and instructions are provided on-screen. As an author, you will be prompted for login and manuscript details as Field of Paper and then to upload your manuscript file(s) according to the instructions.

To avoid postal delays, all transaction is preferred by e-mail. A finished manuscript submission is confirmed by e-mail immediately and your paper enters the editorial process with no postal delays. When a conclusion is made about the publication of your paper by our Editorial Board, revisions can be submitted online with the same procedure, with an occasion to view and respond to all comments.

Complete support for both authors and co-author is provided.

4. MANUSCRIPT’S CATEGORY

Based on potential and nature, the manuscript can be categorized under the following heads:

Original research paper: Such papers are reports of high-level significant original research work.

Review papers: These are concise, significant but helpful and decisive topics for young researchers.

Research articles: These are handled with small investigation and applications

Research letters: The letters are small and concise comments on previously published matters.

5.STRUCTURE AND FORMAT OF MANUSCRIPT

The recommended size of original research paper is less than seven thousand words, review papers fewer than seven thousands words also.Preparation of research paper or how to write research paper, are major hurdle, while writing manuscript. The research articles and research letters should be fewer than three thousand words, the structure original research paper; sometime review paper should be as follows:

Papers: These are reports of significant research (typically less than 7000 words equivalent, including tables, figures, references), and comprise:

(a)Title should be relevant and commensurate with the theme of the paper.

(b) A brief Summary, “Abstract” (less than 150 words) containing the major results and conclusions.

(d) An Introduction, giving necessary background excluding subheadings; objectives must be clearly declared.

(e) Resources and techniques with sufficient complete experimental details (wherever possible by reference) to permit repetition; sources of information must be given and numerical methods must be specified by reference, unless non-standard.

(f) Results should be presented concisely, by well-designed tables and/or figures; the same data may not be used in both; suitable statistical data should be given. All data must be obtained with attention to numerical detail in the planning stage. As reproduced design has been recognized to be important to experiments for a considerable time, the Editor has decided that any paper that appears not to have adequate numerical treatments of the data will be returned un-refereed;

(g) Discussion should cover the implications and consequences, not just recapitulating the results; conclusions should be summarizing.

(h) Brief Acknowledgements.

(i) References in the proper form.

Authors should very cautiously consider the preparation of papers to ensure that they communicate efficiently. Papers are much more likely to be accepted, if they are cautiously designed and laid out, contain few or no errors, are summarizing, and be conventional to the approach and instructions. They will in addition, be published with much less delays than those that require much technical and editorial correction.

The Editorial Board reserves the right to make literary corrections and to make suggestions to improve briefness.

It is vital, that authors take care in submitting a manuscript that is written in simple language and adheres to published guidelines.

Format

Language: The language of publication is UK English. Authors, for whom English is a second language, must have their manuscript efficiently edited by an English-speaking person before submission to make sure that, the English is of high excellence. It is preferable, that manuscripts should be professionally edited.

Standard Usage, Abbreviations, and Units: Spelling and hyphenation should be conventional to The Concise Oxford English Dictionary. Statistics and measurements should at all times be given in figures, e.g. 16 min, except for when the number begins a sentence. When the number does not refer to a unit of measurement it should be spelt in full unless, it is 160 or greater.

Abbreviations supposed to be used carefully. The abbreviated name or expression is supposed to be cited in full at first usage, followed by the conventional abbreviation in parentheses.

Metric SI units are supposed to generally be used excluding where they conflict with current practice or are confusing. For illustration, 1.4 l rather than 1.4 × 10-3 m3, or 4 mm somewhat than 4 × 10-3 m. Chemical formula and solutions must identify the form used, e.g. anhydrous or hydrated, and the concentration must be in clearly defined units. Common species names should be followed by underlines at the first mention. For following use the generic name should be constricted to a single letter, if it is clear.

Structure

All manuscripts submitted to Global Journals Inc. (US), ought to include:

Title: The title page must carry an instructive title that reflects the content, a running title (less than 45 characters together with spaces), names of the authors and co-authors, and the place(s) wherever the work was carried out. The full postal address in addition with the e- mail address of related author must be given. Up to eleven keywords or very brief phrases have to be given to help data retrieval, mining and indexing.

Abstract, used in Original Papers and Reviews:

Optimizing Abstract for Search Engines

Many researchers searching for information online will use search engines such as Google, Yahoo or similar. By optimizing your paper for search engines, you will amplify the chance of someone finding it. This in turn will make it more likely to be viewed and/or cited in a further work. Global Journals Inc. (US) have compiled these guidelines to facilitate you to maximize the web-friendliness of the most public part of your paper.

Key Words

A major linchpin in research work for the writing research paper is the keyword search, which one will employ to find both library and Internet resources.

One must be persistent and creative in using keywords. An effective keyword search requires a strategy and planning a list of possible keywords and phrases to try.

Search engines for most searches, use Boolean searching, which is somewhat different from Internet searches. The Boolean search uses "operators," words (and, or, not, and near) that enable you to expand or narrow your affords. Tips for research paper while preparing research paper are very helpful guideline of research paper.

Choice of key words is first tool of tips to write research paper. Research paper writing is an art.A few tips for deciding as strategically as possible about keyword search:

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• One should start brainstorming lists of possible keywords before even begin searching. Think about the most important concepts related to research work. Ask, "What words would a source have to include to be truly valuable in research paper?" Then consider synonyms for the important words. • It may take the discovery of only one relevant paper to let steer in the right keyword direction because in most databases, the keywords under which a research paper is abstracted are listed with the paper. • One should avoid outdated words.

Keywords are the key that opens a door to research work sources. Keyword searching is an art in which researcher's skills are bound to improve with experience and time.

Numerical Methods: Numerical methods used should be clear and, where appropriate, supported by references.

Acknowledgements: Please make these as concise as possible.

References References follow the Harvard scheme of referencing. References in the text should cite the authors' names followed by the time of their publication, unless there are three or more authors when simply the first author's name is quoted followed by et al. unpublished work has to only be cited where necessary, and only in the text. Copies of references in press in other journals have to be supplied with submitted typescripts. It is necessary that all citations and references be carefully checked before submission, as mistakes or omissions will cause delays.

References to information on the World Wide Web can be given, but only if the information is available without charge to readers on an official site. Wikipedia and Similar websites are not allowed where anyone can change the information. Authors will be asked to make available electronic copies of the cited information for inclusion on the Global Journals Inc. (US) homepage at the judgment of the Editorial Board.

The Editorial Board and Global Journals Inc. (US) recommend that, citation of online-published papers and other material should be done via a DOI (digital object identifier). If an author cites anything, which does not have a DOI, they run the risk of the cited material not being noticeable.

The Editorial Board and Global Journals Inc. (US) recommend the use of a tool such as Reference Manager for reference management and formatting.

Tables, Figures and Figure Legends

Tables: Tables should be few in number, cautiously designed, uncrowned, and include only essential data. Each must have an Arabic number, e.g. Table 4, a self-explanatory caption and be on a separate sheet. Vertical lines should not be used.

Figures: Figures are supposed to be submitted as separate files. Always take in a citation in the text for each figure using Arabic numbers, e.g. Fig. 4. Artwork must be submitted online in electronic form by e-mailing them.

Preparation of Electronic Figures for Publication Even though low quality images are sufficient for review purposes, print publication requires high quality images to prevent the final product being blurred or fuzzy. Submit (or e-mail) EPS (line art) or TIFF (halftone/photographs) files only. MS PowerPoint and Word Graphics are unsuitable for printed pictures. Do not use pixel-oriented software. Scans (TIFF only) should have a resolution of at least 350 dpi (halftone) or 700 to 1100 dpi (line drawings) in relation to the imitation size. Please give the data for figures in black and white or submit a Color Work Agreement Form. EPS files must be saved with fonts embedded (and with a TIFF preview, if possible).

For scanned images, the scanning resolution (at final image size) ought to be as follows to ensure good reproduction: line art: >650 dpi; halftones (including gel photographs) : >350 dpi; figures containing both halftone and line images: >650 dpi.

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Figure Legends: Self-explanatory legends of all figures should be incorporated separately under the heading 'Legends to Figures'. In the full-text online edition of the journal, figure legends may possibly be truncated in abbreviated links to the full screen version. Therefore, the first 100 characters of any legend should notify the reader, about the key aspects of the figure.

6. AFTER ACCEPTANCE

Upon approval of a paper for publication, the manuscript will be forwarded to the dean, who is responsible for the publication of the Global Journals Inc. (US).

6.1 Proof Corrections The corresponding author will receive an e-mail alert containing a link to a website or will be attached. A working e-mail address must therefore be provided for the related author.

Acrobat Reader will be required in order to read this file. This software can be downloaded

(Free of charge) from the following website: www.adobe.com/products/acrobat/readstep2.html. This will facilitate the file to be opened, read on screen, and printed out in order for any corrections to be added. Further instructions will be sent with the proof.

Proofs must be returned to the dean at [email protected] within three days of receipt.

As changes to proofs are costly, we inquire that you only correct typesetting errors. All illustrations are retained by the publisher. Please note that the authors are responsible for all statements made in their work, including changes made by the copy editor.

6.2 Early View of Global Journals Inc. (US) (Publication Prior to Print) The Global Journals Inc. (US) are enclosed by our publishing's Early View service. Early View articles are complete full-text articles sent in advance of their publication. Early View articles are absolute and final. They have been completely reviewed, revised and edited for publication, and the authors' final corrections have been incorporated. Because they are in final form, no changes can be made after sending them. The nature of Early View articles means that they do not yet have volume, issue or page numbers, so Early View articles cannot be cited in the conventional way.

6.3 Author Services Online production tracking is available for your article through Author Services. Author Services enables authors to track their article - once it has been accepted - through the production process to publication online and in print. Authors can check the status of their articles online and choose to receive automated e-mails at key stages of production. The authors will receive an e-mail with a unique link that enables them to register and have their article automatically added to the system. Please ensure that a complete e-mail address is provided when submitting the manuscript.

6.4 Author Material Archive Policy Please note that if not specifically requested, publisher will dispose off hardcopy & electronic information submitted, after the two months of publication. If you require the return of any information submitted, please inform the Editorial Board or dean as soon as possible.

6.5 Offprint and Extra Copies A PDF offprint of the online-published article will be provided free of charge to the related author, and may be distributed according to the Publisher's terms and conditions. Additional paper offprint may be ordered by emailing us at: [email protected] .

You must strictly follow above Author Guidelines before submitting your paper or else we will not at all be responsible for any corrections in future in any of the way.

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Before start writing a good quality Computer Science Research Paper, let us first understand what is Computer Science Research Paper? So, Computer Science Research Paper is the paper which is written by professionals or scientists who are associated to Computer Science and Information Technology, or doing research study in these areas. If you are novel to this field then you can consult about this field from your supervisor or guide.

TECHNIQUES FOR WRITING A GOOD QUALITY RESEARCH PAPER:

1. Choosing the topic: In most cases, the topic is searched by the interest of author but it can be also suggested by the guides. You can have several topics and then you can judge that in which topic or subject you are finding yourself most comfortable. This can be done by asking several questions to yourself, like Will I be able to carry our search in this area? Will I find all necessary recourses to accomplish the search? Will I be able to find all information in this field area? If the answer of these types of questions will be "Yes" then you can choose that topic. In most of the cases, you may have to conduct the surveys and have to visit several places because this field is related to Computer Science and Information Technology. Also, you may have to do a lot of work to find all rise and falls regarding the various data of that subject. Sometimes, detailed information plays a vital role, instead of short information.

2. Evaluators are human: First thing to remember that evaluators are also human being. They are not only meant for rejecting a paper. They are here to evaluate your paper. So, present your Best.

3. Think Like Evaluators: If you are in a confusion or getting demotivated that your paper will be accepted by evaluators or not, then think and try to evaluate your paper like an Evaluator. Try to understand that what an evaluator wants in your research paper and automatically you will have your answer.

4. Make blueprints of paper: The outline is the plan or framework that will help you to arrange your thoughts. It will make your paper logical. But remember that all points of your outline must be related to the topic you have chosen.

5. Ask your Guides: If you are having any difficulty in your research, then do not hesitate to share your difficulty to your guide (if you have any). They will surely help you out and resolve your doubts. If you can't clarify what exactly you require for your work then ask the supervisor to help you with the alternative. He might also provide you the list of essential readings.

6. Use of computer is recommended: As you are doing research in the field of Computer Science, then this point is quite obvious.

7. Use right software: Always use good quality software packages. If you are not capable to judge good software then you can lose quality of your paper unknowingly. There are various software programs available to help you, which you can get through Internet.

8. Use the Internet for help: An excellent start for your paper can be by using the Google. It is an excellent search engine, where you can have your doubts resolved. You may also read some answers for the frequent question how to write my research paper or find model research paper. From the internet library you can download books. If you have all required books make important reading selecting and analyzing the specified information. Then put together research paper sketch out.

9. Use and get big pictures: Always use encyclopedias, Wikipedia to get pictures so that you can go into the depth.

10. Bookmarks are useful: When you read any book or magazine, you generally use bookmarks, right! It is a good habit, which helps to not to lose your continuity. You should always use bookmarks while searching on Internet also, which will make your search easier.

11. Revise what you wrote: When you write anything, always read it, summarize it and then finalize it.

12. Make all efforts: Make all efforts to mention what you are going to write in your paper. That means always have a good start. Try to mention everything in introduction, that what is the need of a particular research paper. Polish your work by good skill of writing and always give an evaluator, what he wants.

13. Have backups: When you are going to do any important thing like making research paper, you should always have backup copies of it either in your computer or in paper. This will help you to not to lose any of your important.

14. Produce good diagrams of your own: Always try to include good charts or diagrams in your paper to improve quality. Using several and unnecessary diagrams will degrade the quality of your paper by creating "hotchpotch." So always, try to make and include those diagrams, which are made by your own to improve readability and understandability of your paper.

15. Use of direct quotes: When you do research relevant to literature, history or current affairs then use of quotes become essential but if study is relevant to science then use of quotes is not preferable.

16. Use proper verb tense: Use proper verb tenses in your paper. Use past tense, to present those events that happened. Use present tense to indicate events that are going on. Use future tense to indicate future happening events. Use of improper and wrong tenses will confuse the evaluator. Avoid the sentences that are incomplete.

17. Never use online paper: If you are getting any paper on Internet, then never use it as your research paper because it might be possible that evaluator has already seen it or maybe it is outdated version.

18. Pick a good study spot: To do your research studies always try to pick a spot, which is quiet. Every spot is not for studies. Spot that suits you choose it and proceed further.

19. Know what you know: Always try to know, what you know by making objectives. Else, you will be confused and cannot achieve your target.

20. Use good quality grammar: Always use a good quality grammar and use words that will throw positive impact on evaluator. Use of good quality grammar does not mean to use tough words, that for each word the evaluator has to go through dictionary. Do not start sentence with a conjunction. Do not fragment sentences. Eliminate one-word sentences. Ignore passive voice. Do not ever use a big word when a diminutive one would suffice. Verbs have to be in agreement with their subjects. Prepositions are not expressions to finish sentences with. It is incorrect to ever divide an infinitive. Avoid clichés like the disease. Also, always shun irritating alliteration. Use language that is simple and straight forward. put together a neat summary.

21. Arrangement of information: Each section of the main body should start with an opening sentence and there should be a changeover at the end of the section. Give only valid and powerful arguments to your topic. You may also maintain your arguments with records.

22. Never start in last minute: Always start at right time and give enough time to research work. Leaving everything to the last minute will degrade your paper and spoil your work.

23. Multitasking in research is not good: Doing several things at the same time proves bad habit in case of research activity. Research is an area, where everything has a particular time slot. Divide your research work in parts and do particular part in particular time slot.

24. Never copy others' work: Never copy others' work and give it your name because if evaluator has seen it anywhere you will be in trouble.

25. Take proper rest and food: No matter how many hours you spend for your research activity, if you are not taking care of your health then all your efforts will be in vain. For a quality research, study is must, and this can be done by taking proper rest and food.

26. Go for seminars: Attend seminars if the topic is relevant to your research area. Utilize all your resources.

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27. Refresh your mind after intervals: Try to give rest to your mind by listening to soft music or by sleeping in intervals. This will also improve your memory.

28. Make colleagues: Always try to make colleagues. No matter how sharper or intelligent you are, if you make colleagues you can have several ideas, which will be helpful for your research.

29. Think technically: Always think technically. If anything happens, then search its reasons, its benefits, and demerits.

30. Think and then print: When you will go to print your paper, notice that tables are not be split, headings are not detached from their descriptions, and page sequence is maintained.

31. Adding unnecessary information: Do not add unnecessary information, like, I have used MS Excel to draw graph. Do not add irrelevant and inappropriate material. These all will create superfluous. Foreign terminology and phrases are not apropos. One should NEVER take a broad view. Analogy in script is like feathers on a snake. Not at all use a large word when a very small one would be sufficient. Use words properly, regardless of how others use them. Remove quotations. Puns are for kids, not grunt readers. Amplification is a billion times of inferior quality than sarcasm.

32. Never oversimplify everything: To add material in your research paper, never go for oversimplification. This will definitely irritate the evaluator. Be more or less specific. Also too, by no means, ever use rhythmic redundancies. Contractions aren't essential and shouldn't be there used. Comparisons are as terrible as clichés. Give up ampersands and abbreviations, and so on. Remove commas, that are, not necessary. Parenthetical words however should be together with this in commas. Understatement is all the time the complete best way to put onward earth-shaking thoughts. Give a detailed literary review.

33. Report concluded results: Use concluded results. From raw data, filter the results and then conclude your studies based on measurements and observations taken. Significant figures and appropriate number of decimal places should be used. Parenthetical remarks are prohibitive. Proofread carefully at final stage. In the end give outline to your arguments. Spot out perspectives of further study of this subject. Justify your conclusion by at the bottom of them with sufficient justifications and examples.

34. After conclusion: Once you have concluded your research, the next most important step is to present your findings. Presentation is extremely important as it is the definite medium though which your research is going to be in print to the rest of the crowd. Care should be taken to categorize your thoughts well and present them in a logical and neat manner. A good quality research paper format is essential because it serves to highlight your research paper and bring to light all necessary aspects in your research.

,1)250$/*8,'(/,1(62)5(6($5&+3$3(5:5,7,1* Key points to remember:

Submit all work in its final form. Write your paper in the form, which is presented in the guidelines using the template. Please note the criterion for grading the final paper by peer-reviewers.

Final Points:

A purpose of organizing a research paper is to let people to interpret your effort selectively. The journal requires the following sections, submitted in the order listed, each section to start on a new page.

The introduction will be compiled from reference matter and will reflect the design processes or outline of basis that direct you to make study. As you will carry out the process of study, the method and process section will be constructed as like that. The result segment will show related statistics in nearly sequential order and will direct the reviewers next to the similar intellectual paths throughout the data that you took to carry out your study. The discussion section will provide understanding of the data and projections as to the implication of the results. The use of good quality references all through the paper will give the effort trustworthiness by representing an alertness of prior workings.

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Writing a research paper is not an easy job no matter how trouble-free the actual research or concept. Practice, excellent preparation, and controlled record keeping are the only means to make straightforward the progression.

General style:

Specific editorial column necessities for compliance of a manuscript will always take over from directions in these general guidelines.

To make a paper clear

· Adhere to recommended page limits

Mistakes to evade

Insertion a title at the foot of a page with the subsequent text on the next page Separating a table/chart or figure - impound each figure/table to a single page Submitting a manuscript with pages out of sequence

In every sections of your document

· Use standard writing style including articles ("a", "the," etc.)

· Keep on paying attention on the research topic of the paper

· Use paragraphs to split each significant point (excluding for the abstract)

· Align the primary line of each section

· Present your points in sound order

· Use present tense to report well accepted

· Use past tense to describe specific results

· Shun familiar wording, don't address the reviewer directly, and don't use slang, slang language, or superlatives

· Shun use of extra pictures - include only those figures essential to presenting results

Title Page:

Choose a revealing title. It should be short. It should not have non-standard acronyms or abbreviations. It should not exceed two printed lines. It should include the name(s) and address (es) of all authors.

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Abstract:

The summary should be two hundred words or less. It should briefly and clearly explain the key findings reported in the manuscript-- must have precise statistics. It should not have abnormal acronyms or abbreviations. It should be logical in itself. Shun citing references at this point.

An abstract is a brief distinct paragraph summary of finished work or work in development. In a minute or less a reviewer can be taught the foundation behind the study, common approach to the problem, relevant results, and significant conclusions or new questions.

Write your summary when your paper is completed because how can you write the summary of anything which is not yet written? Wealth of terminology is very essential in abstract. Yet, use comprehensive sentences and do not let go readability for briefness. You can maintain it succinct by phrasing sentences so that they provide more than lone rationale. The author can at this moment go straight to shortening the outcome. Sum up the study, wi th the subsequent elements in any summa ry. Try to maintain the initial two items to no more than one ruling each.

Reason of the study - theory, overall issue, purpose Fundamental goal To the point depiction of the research Consequences, including definite statistics - if the consequences are quantitative in nature, account quantitative data; results of any numerical analysis should be reported Significant conclusions or questions that track from the research(es)

Approach:

Single section, and succinct As a outline of job done, it is always written in past tense A conceptual should situate on its own, and not submit to any other part of the paper such as a form or table Center on shortening results - bound background information to a verdict or two, if completely necessary What you account in an conceptual must be regular with what you reported in the manuscript Exact spelling, clearness of sentences and phrases, and appropriate reporting of quantities (proper units, important statistics) are just as significant in an abstract as they are anywhere else

Introduction: The Introduction should "introduce" the manuscript. The reviewer should be presented with sufficient background information to be capable to comprehend and calculate the purpose of your study without having to submit to other works. The basis for the study should be offered. Give most important references but shun difficult to make a comprehensive appraisal of the topic. In the introduction, describe the problem visibly. If the problem is not acknowledged in a logical, reasonable way, the reviewer will have no attention in your result. Speak in common terms about techniques used to explain the problem, if needed, but do not present any particulars about the protocols here. Following approach can create a valuable beginning:

Explain the value (significance) of the study Shield the model - why did you employ this particular system or method? What is its compensation? You strength remark on its appropriateness from a abstract point of vision as well as point out sensible reasons for using it. Present a justification. Status your particular theory (es) or aim(s), and describe the logic that led you to choose them. Very for a short time explain the tentative propose and how it skilled the declared objectives.

Approach:

Use past tense except for when referring to recognized facts. After all, the manuscript will be submitted after the entire job is done. Sort out your thoughts; manufacture one key point with every section. If you make the four points listed above, you will need a least of four paragraphs.

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Present surroundings information only as desirable in order hold up a situation. The reviewer does not desire to read the whole thing you know about a topic. Shape the theory/purpose specifically - do not take a broad view. As always, give awareness to spelling, simplicity and correctness of sentences and phrases.

Procedures (Methods and Materials):

This part is supposed to be the easiest to carve if you have good skills. A sound written Procedures segment allows a capable scientist to replacement your results. Present precise information about your supplies. The suppliers and clarity of reagents can be helpful bits of information. Present methods in sequential order but linked methodologies can be grouped as a segment. Be concise when relating the protocols. Attempt for the least amount of information that would permit another capable scientist to spare your outcome but be cautious that vital information is integrated. The use of subheadings is suggested and ought to be synchronized with the results section. When a technique is used that has been well described in another object, mention the specific item describing a way but draw the basic principle while stating the situation. The purpose is to text all particular resources and broad procedures, so that another person may use some or all of the methods in one more study or referee the scientific value of your work. It is not to be a step by step report of the whole thing you did, nor is a methods section a set of orders.

Materials: Explain materials individually only if the study is so complex that it saves liberty this way. Embrace particular materials, and any tools or provisions that are not frequently found in laboratories. Do not take in frequently found. If use of a definite type of tools. Materials may be reported in a part section or else they may be recognized along with your measures.

Methods:

Report the method (not particulars of each process that engaged the same methodology) Describe the method entirely To be succinct, present methods under headings dedicated to specific dealings or groups of measures Simplify - details how procedures were completed not how they were exclusively performed on a particular day. If well known procedures were used, account the procedure by name, possibly with reference, and that's all.

Approach:

It is embarrassed or not possible to use vigorous voice when documenting methods with no using first person, which would focus the reviewer's interest on the researcher rather than the job. As a result when script up the methods most authors use third person passive voice. Use standard style in this and in every other part of the paper - avoid familiar lists, and use full sentences.

What to keep away from

Resources and methods are not a set of information. Skip all descriptive information and surroundings - save it for the argument. Leave out information that is immaterial to a third party.

Results:

The principle of a results segment is to present and demonstrate your conclusion. Create this part a entirely objective details of the outcome, and save all understanding for the discussion.

The page length of this segment is set by the sum and types of data to be reported. Carry on to be to the point, by means of statistics and tables, if suitable, to present consequences most efficiently.You must obviously differentiate material that would usually be incorporated in a study editorial from any unprocessed data or additional appendix matter that would not be available. In fact, such matter should not be submitted at all except requested by the instructor.

Content

Sum up your conclusion in text and demonstrate them, if suitable, with figures and tables. In manuscript, explain each of your consequences, point the reader to remarks that are most appropriate. Present a background, such as by describing the question that was addressed by creation an exacting study. Explain results of control experiments and comprise remarks that are not accessible in a prescribed figure or table, if appropriate. Examine your data, then prepare the analyzed (transformed) data in the form of a figure (graph), table, or in manuscript form. What to stay away from Do not discuss or infer your outcome, report surroundings information, or try to explain anything. Not at all, take in raw data or intermediate calculations in a research manuscript. Do not present the similar data more than once. Manuscript should complement any figures or tables, not duplicate the identical information. Never confuse figures with tables - there is a difference. Approach As forever, use past tense when you submit to your results, and put the whole thing in a reasonable order. Put figures and tables, appropriately numbered, in order at the end of the report If you desire, you may place your figures and tables properly within the text of your results part. Figures and tables If you put figures and tables at the end of the details, make certain that they are visibly distinguished from any attach appendix materials, such as raw facts Despite of position, each figure must be numbered one after the other and complete with subtitle In spite of position, each table must be titled, numbered one after the other and complete with heading All figure and table must be adequately complete that it could situate on its own, divide from text Discussion:

The Discussion is expected the trickiest segment to write and describe. A lot of papers submitted for journal are discarded based on problems with the Discussion. There is no head of state for how long a argument should be. Position your understanding of the outcome visibly to lead the reviewer through your conclusions, and then finish the paper with a summing up of the implication of the study. The purpose here is to offer an understanding of your results and hold up for all of your conclusions, using facts from your research and generally accepted information, if suitable. The implication of result should be visibly described. Infer your data in the conversation in suitable depth. This means that when you clarify an observable fact you must explain mechanisms that may account for the observation. If your results vary from your prospect, make clear why that may have happened. If your results agree, then explain the theory that the proof supported. It is never suitable to just state that the data approved with prospect, and let it drop at that.

Make a decision if each premise is supported, discarded, or if you cannot make a conclusion with assurance. Do not just dismiss a study or part of a study as "uncertain." Research papers are not acknowledged if the work is imperfect. Draw what conclusions you can based upon the results that you have, and take care of the study as a finished work You may propose future guidelines, such as how the experiment might be personalized to accomplish a new idea. Give details all of your remarks as much as possible, focus on mechanisms. Make a decision if the tentative design sufficiently addressed the theory, and whether or not it was correctly restricted. Try to present substitute explanations if sensible alternatives be present. One research will not counter an overall question, so maintain the large picture in mind, where do you go next? The best studies unlock new avenues of study. What questions remain? Recommendations for detailed papers will offer supplementary suggestions. Approach:

When you refer to information, differentiate data generated by your own studies from available information Submit to work done by specific persons (including you) in past tense. Submit to generally acknowledged facts and main beliefs in present tense.

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THE $'0,1,675$7,2158/(6

Please carefully note down following rules and regulation before submitting your Research Paper to Global Journals Inc. (US):

Segment Draft and Final Research Paper: You have to strictly follow the template of research paper. If it is not done your paper may get rejected.

The major constraint is that you must independently make all content, tables, graphs, and facts that are offered in the paper. You must write each part of the paper wholly on your own. The Peer-reviewers need to identify your own perceptive of the concepts in your own terms. NEVER extract straight from any foundation, and never rephrase someone else's analysis.

Do not give permission to anyone else to "PROOFREAD" your manuscript.

Methods to avoid Plagiarism is applied by us on every paper, if found guilty, you will be blacklisted by all of our collaborated research groups, your institution will be informed for this and strict legal actions will be taken immediately.) To guard yourself and others from possible illegal use please do not permit anyone right to use to your paper and files.

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CRITERION FOR GRADING A RESEARCH PAPER (COMPILATION) BY GLOBAL JOURNALS INC. (US) Please note that following table is only a Grading of "Paper Compilation" and not on "Performed/Stated Research" whose grading solely depends on Individual Assigned Peer Reviewer and Editorial Board Member. These can be available only on request and after decision of Paper. This report will be the property of Global Journals Inc. (US).

Topics Grades

A-B C-D E-F

Clear and concise with Unclear summary and no No specific data with ambiguous appropriate content, Correct specific data, Incorrect form information Abstract format. 200 words or below Above 200 words Above 250 words

Containing all background Unclear and confusing data, Out of place depth and content, details with clear goal and appropriate format, grammar hazy format appropriate details, flow and spelling errors with specification, no grammar unorganized matter Introduction and spelling mistake, well organized sentence and paragraph, reference cited

Clear and to the point with Difficult to comprehend with Incorrect and unorganized well arranged paragraph, embarrassed text, too much structure with hazy meaning Methods and precision and accuracy of explanation but completed Procedures facts and figures, well organized subheads

Well organized, Clear and Complete and embarrassed Irregular format with wrong facts specific, Correct units with text, difficult to comprehend and figures precision, correct data, well Result structuring of paragraph, no grammar and spelling mistake

Well organized, meaningful Wordy, unclear conclusion, Conclusion is not cited, specification, sound spurious unorganized, difficult to conclusion, logical and comprehend concise explanation, highly Discussion structured paragraph reference cited

Complete and correct Beside the point, Incomplete Wrong format and structuring References format, well organized

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Index

Chirality · 38

Instantaneous · 1

Landauer · 41, 42 Levenberg · 12

Memoutdata · 24

Neurons · 5, 6, 7, 12

Spectrog · 28

Tonals · 36 Transconductance · 38, 42, 43

Wallies · 13, 20

Zirconia · 38, 43

Global Journals